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Author SHA1 Message Date
Marek Lemańczyk 6027a73839 Split GPU heuristic tables by scope 2025-11-01 09:22:44 +01:00
127 changed files with 8088 additions and 8882 deletions

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+1 -3
View File
@@ -9,7 +9,5 @@
"Mersenne",
"primality",
"suff"
],
"geminicodeassist.project": "evenperfectbitscanner",
"todo-tree.tree.showCountsInTree": true
]
}
@@ -1,3 +1,4 @@
using System;
using System.Runtime.CompilerServices;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
@@ -1,5 +1,6 @@
using System.Runtime.CompilerServices;
using BenchmarkDotNet.Attributes;
using PerfectNumbers.Core;
using BenchmarkDotNet.Jobs;
namespace EvenPerfectBitScanner.Benchmarks;
@@ -1,3 +1,5 @@
using System;
using System.Collections.Generic;
using System.Runtime.CompilerServices;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
@@ -1,3 +1,5 @@
using System;
using System.Collections.Generic;
using System.Runtime.CompilerServices;
using BenchmarkDotNet.Attributes;
using PerfectNumbers.Core;
@@ -1,3 +1,5 @@
using System;
using System.Collections.Generic;
using System.Runtime.CompilerServices;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
@@ -1,3 +1,5 @@
using System;
using System.Collections.Generic;
using System.Runtime.CompilerServices;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
@@ -1,3 +1,5 @@
using System;
using System.Collections.Generic;
using System.Runtime.CompilerServices;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
@@ -1,3 +1,5 @@
using System;
using System.Collections.Generic;
using System.Runtime.CompilerServices;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
@@ -1,3 +1,5 @@
using System;
using System.Collections.Generic;
using System.Runtime.CompilerServices;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
@@ -1,3 +1,5 @@
using System;
using System.Collections.Generic;
using System.Runtime.CompilerServices;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
@@ -1,3 +1,5 @@
using System;
using System.Collections.Generic;
using System.Runtime.CompilerServices;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
@@ -1,3 +1,5 @@
using System;
namespace EvenPerfectBitScanner.Benchmarks;
public enum ModNumericType
@@ -1,3 +1,4 @@
using System;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
@@ -1,8 +1,12 @@
using System;
using System.Collections.Generic;
using System.Linq;
using System.Runtime.CompilerServices;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
using ILGPU;
using ILGPU.Runtime;
using PerfectNumbers.Core;
using PerfectNumbers.Core.Gpu;
namespace EvenPerfectBitScanner.Benchmarks;
@@ -1,3 +1,4 @@
using System;
using System.Buffers.Binary;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
@@ -100,7 +101,7 @@ public class Pow2ModBenchmarks
for (int i = 0; i < SampleCount; i++)
{
checksum ^= exponents[i].Pow2MontgomeryModWindowedConvertGpu(divisors[i]);
checksum ^= exponents[i].Pow2MontgomeryModWindowedGpu(divisors[i], keepMontgomery: false);
}
return checksum;
@@ -77,7 +77,7 @@ public class Pow2MontgomeryModBenchmarks
for (int i = 0; i < SampleCount; i++)
{
checksum ^= exponents[i].Pow2MontgomeryModWindowedConvertGpu(divisors[i]);
checksum ^= exponents[i].Pow2MontgomeryModWindowedGpu(divisors[i], keepMontgomery: false);
}
return checksum;
@@ -1,3 +1,4 @@
using System;
using PerfectNumbers.Core;
namespace EvenPerfectBitScanner.Benchmarks;
@@ -1,3 +1,4 @@
using System;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
using PerfectNumbers.Core;
@@ -33,7 +34,7 @@ public class Pow2MontgomeryModWindowedKeepMontgomeryGpuBenchmarks
for (int i = 0; i < cases.Length; i++)
{
ref readonly Pow2MontgomeryModWindowedBenchmarkCase current = ref cases[i];
checksum ^= current.Exponent.Pow2MontgomeryModWindowedConvertGpu(current.Divisor);
checksum ^= current.Exponent.Pow2MontgomeryModWindowedGpu(current.Divisor, keepMontgomery: false);
}
return checksum;
@@ -51,7 +52,7 @@ public class Pow2MontgomeryModWindowedKeepMontgomeryGpuBenchmarks
for (int i = 0; i < cases.Length; i++)
{
ref readonly Pow2MontgomeryModWindowedBenchmarkCase current = ref cases[i];
checksum ^= current.Exponent.Pow2MontgomeryModWindowedKeepGpu(current.Divisor);
checksum ^= current.Exponent.Pow2MontgomeryModWindowedGpu(current.Divisor, keepMontgomery: true);
}
return checksum;
@@ -1,8 +1,10 @@
using System;
using System.Collections.Generic;
using System.Threading;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
using Open.Numeric.Primes;
using PerfectNumbers.Core;
using PerfectNumbers.Core.Gpu.Accelerators;
namespace EvenPerfectBitScanner.Benchmarks;
@@ -10,6 +12,7 @@ namespace EvenPerfectBitScanner.Benchmarks;
[MemoryDiagnoser]
public class PrimeTesterBenchmarks
{
private static readonly HeuristicCombinedPrimeTester _heuristicCombinedTester = new();
private static readonly HeuristicPrimeTester _heuristicTester = new();
private ulong[] _candidates = [];
@@ -26,14 +29,12 @@ public class PrimeTesterBenchmarks
return;
}
PrimeOrderCalculatorAccelerator.WarmUp();
// HeuristicGroupABPrimeTesterAccelerator.WarmUp();
_ = HeuristicPrimeTester.IsPrimeCpu(_candidates[0]);
_ = HeuristicPrimeTester.IsPrimeGpu(_candidates[0]);
_ = _heuristicTester.IsPrimeCpu(_candidates[0]);
_ = _heuristicTester.IsPrimeGpu(_candidates[0]);
_ = Prime.Numbers.IsPrime(_candidates[0]);
}
// [Benchmark]
[Benchmark(Baseline = true)]
public int HeuristicCpu()
{
HeuristicPrimeTester tester = _heuristicTester;
@@ -42,7 +43,7 @@ public class PrimeTesterBenchmarks
for (int i = 0; i < values.Length; i++)
{
if (HeuristicPrimeTester.IsPrimeCpu(values[i]))
if (tester.IsPrimeCpu(values[i]))
{
primeCount++;
}
@@ -60,7 +61,7 @@ public class PrimeTesterBenchmarks
for (int i = 0; i < values.Length; i++)
{
if (HeuristicPrimeTester.IsPrimeGpu(values[i]))
if (tester.IsPrimeGpu(values[i]))
{
primeCount++;
}
@@ -103,15 +104,18 @@ public class PrimeTesterBenchmarks
return primeCount;
}
private static readonly PrimeTester _nonHeuristicTester = new();
[Benchmark]
public int NonHeuristicGpu()
{
PrimeTester tester = _nonHeuristicTester;
ulong[] values = _candidates;
int primeCount = 0;
for (int i = 0; i < values.Length; i++)
{
if (PrimeTester.IsPrimeGpu(values[i]))
if (tester.IsPrimeGpu(values[i]))
{
primeCount++;
}
@@ -120,7 +124,7 @@ public class PrimeTesterBenchmarks
return primeCount;
}
[Benchmark(Baseline = true)]
[Benchmark]
public int NonHeuristicCpu()
{
ulong[] values = _candidates;
@@ -137,7 +141,7 @@ public class PrimeTesterBenchmarks
return primeCount;
}
// [Benchmark]
[Benchmark]
public int OpenNumericPrimes()
{
ulong[] values = _candidates;
@@ -19,7 +19,7 @@ internal static class Program
"/help"
};
private const string DefaultHeader = "p,divisor,searchedMersenne,detailedCheck,passedAllTests";
private const string DefaultHeader = "p,searchedMersenne,detailedCheck,passedAllTests";
private static int Main(string[] args)
{
@@ -3,9 +3,13 @@ using Xunit;
using System.Reflection;
using PerfectNumbers.Core;
using PerfectNumbers.Core.Gpu;
using EvenPerfectBitScanner;
using EvenPerfectBitScanner.Candidates;
using EvenPerfectBitScanner.Candidates.Transforms;
using System.Numerics;
using System.Threading;
using System.Threading.Tasks;
namespace EvenPerfectBitScanner.Tests;
@@ -98,11 +102,13 @@ public class ProgramTests
var testerField = typeof(Program).GetField("_divisorTester", BindingFlags.NonPublic | BindingFlags.Static)!;
var candidatesField = typeof(MersenneNumberDivisorGpuTester).GetField("_divisorCandidates", BindingFlags.NonPublic | BindingFlags.Static)!;
var primeField = typeof(Program).GetField("PrimeTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var forceCpuProp = typeof(GpuContextPool).GetProperty("ForceCpu");
testerField.SetValue(null, new MersenneNumberDivisorGpuTester());
primeField.SetValue(null, new ThreadLocal<PrimeTester>(() => new PrimeTester(), trackAllValues: true));
CandidatesCalculator.OverrideResidueTrackers(new ThreadLocal<ModResidueTracker>(() => new ModResidueTracker(ResidueModel.Identity, 2UL, true), trackAllValues: true));
candidatesField.SetValue(null, new (ulong, uint)[] { (7UL, 3U), (23UL, 11U) });
forceCpuProp!.SetValue(null, true);
try
{
@@ -116,6 +122,7 @@ public class ProgramTests
candidatesField.SetValue(null, null);
primeField.SetValue(null, null);
CandidatesCalculator.ResetResidueTrackers();
forceCpuProp!.SetValue(null, false);
ResetCliArguments();
}
}
@@ -128,11 +135,13 @@ public class ProgramTests
var testerField = typeof(Program).GetField("_divisorTester", BindingFlags.NonPublic | BindingFlags.Static)!;
var candidatesField = typeof(MersenneNumberDivisorGpuTester).GetField("_divisorCandidates", BindingFlags.NonPublic | BindingFlags.Static)!;
var primeField = typeof(Program).GetField("PrimeTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var forceCpuProp = typeof(GpuContextPool).GetProperty("ForceCpu");
testerField.SetValue(null, new MersenneNumberDivisorGpuTester());
primeField.SetValue(null, new ThreadLocal<PrimeTester>(() => new PrimeTester(), trackAllValues: true));
CandidatesCalculator.OverrideResidueTrackers(new ThreadLocal<ModResidueTracker>(() => new ModResidueTracker(ResidueModel.Identity, 2UL, true), trackAllValues: true));
candidatesField.SetValue(null, Array.Empty<(ulong, uint)>());
forceCpuProp!.SetValue(null, true);
try
{
@@ -146,6 +155,7 @@ public class ProgramTests
candidatesField.SetValue(null, null);
primeField.SetValue(null, null);
CandidatesCalculator.ResetResidueTrackers();
forceCpuProp!.SetValue(null, false);
ResetCliArguments();
}
}
@@ -158,10 +168,12 @@ public class ProgramTests
var testerField = typeof(Program).GetField("_divisorTester", BindingFlags.NonPublic | BindingFlags.Static)!;
var primeField = typeof(Program).GetField("PrimeTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var forceCpuProp = typeof(GpuContextPool).GetProperty("ForceCpu");
testerField.SetValue(null, new MersenneNumberDivisorGpuTester());
primeField.SetValue(null, new ThreadLocal<PrimeTester>(() => new PrimeTester(), trackAllValues: true));
CandidatesCalculator.OverrideResidueTrackers(new ThreadLocal<ModResidueTracker>(() => new ModResidueTracker(ResidueModel.Identity, 2UL, true), trackAllValues: true));
forceCpuProp!.SetValue(null, true);
try
{
@@ -174,6 +186,7 @@ public class ProgramTests
testerField.SetValue(null, null);
primeField.SetValue(null, null);
CandidatesCalculator.ResetResidueTrackers();
forceCpuProp!.SetValue(null, false);
ResetCliArguments();
}
}
@@ -186,10 +199,12 @@ public class ProgramTests
var testerField = typeof(Program).GetField("_divisorTester", BindingFlags.NonPublic | BindingFlags.Static)!;
var primeField = typeof(Program).GetField("PrimeTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var forceCpuProp = typeof(GpuContextPool).GetProperty("ForceCpu");
testerField.SetValue(null, new MersenneNumberDivisorGpuTester());
primeField.SetValue(null, new ThreadLocal<PrimeTester>(() => new PrimeTester(), trackAllValues: true));
CandidatesCalculator.OverrideResidueTrackers(new ThreadLocal<ModResidueTracker>(() => new ModResidueTracker(ResidueModel.Identity, 2UL, true), trackAllValues: true));
forceCpuProp!.SetValue(null, false);
try
{
@@ -206,6 +221,7 @@ public class ProgramTests
testerField.SetValue(null, null);
primeField.SetValue(null, null);
CandidatesCalculator.ResetResidueTrackers();
forceCpuProp!.SetValue(null, false);
ResetCliArguments();
}
}
@@ -217,10 +233,12 @@ public class ProgramTests
var mersenneField = typeof(Program).GetField("MersenneTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var primeField = typeof(Program).GetField("PrimeTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var forceCpuProp = typeof(GpuContextPool).GetProperty("ForceCpu");
mersenneField.SetValue(null, new ThreadLocal<MersenneNumberTester>(() => new MersenneNumberTester(useIncremental: true, useResidue: true, maxK: 1_000UL), trackAllValues: true));
primeField.SetValue(null, new ThreadLocal<PrimeTester>(() => new PrimeTester(), trackAllValues: true));
CandidatesCalculator.OverrideResidueTrackers(new ThreadLocal<ModResidueTracker>(() => new ModResidueTracker(ResidueModel.Identity, 2UL, true), trackAllValues: true));
forceCpuProp!.SetValue(null, false);
try
{
@@ -237,6 +255,7 @@ public class ProgramTests
mersenneField.SetValue(null, null);
primeField.SetValue(null, null);
CandidatesCalculator.ResetResidueTrackers();
forceCpuProp!.SetValue(null, false);
ResetCliArguments();
}
}
@@ -248,6 +267,7 @@ public class ProgramTests
var mersenneField = typeof(Program).GetField("MersenneTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var primeField = typeof(Program).GetField("PrimeTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var forceCpuProp = typeof(GpuContextPool).GetProperty("ForceCpu");
mersenneField.SetValue(null, new ThreadLocal<MersenneNumberTester>(() => new MersenneNumberTester(
useIncremental: true,
@@ -255,6 +275,7 @@ public class ProgramTests
maxK: 1_024UL), trackAllValues: true));
primeField.SetValue(null, new ThreadLocal<PrimeTester>(() => new PrimeTester(), trackAllValues: true));
CandidatesCalculator.OverrideResidueTrackers(new ThreadLocal<ModResidueTracker>(() => new ModResidueTracker(ResidueModel.Identity, 2UL, true), trackAllValues: true));
forceCpuProp!.SetValue(null, false);
try
{
@@ -271,6 +292,7 @@ public class ProgramTests
mersenneField.SetValue(null, null);
primeField.SetValue(null, null);
CandidatesCalculator.ResetResidueTrackers();
forceCpuProp!.SetValue(null, false);
ResetCliArguments();
}
}
@@ -283,6 +305,7 @@ public class ProgramTests
var mersenneField = typeof(Program).GetField("MersenneTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var primeField = typeof(Program).GetField("PrimeTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var forceCpuProp = typeof(GpuContextPool).GetProperty("ForceCpu");
mersenneField.SetValue(null, new ThreadLocal<MersenneNumberTester>(() => new MersenneNumberTester(
useIncremental: true,
@@ -290,6 +313,7 @@ public class ProgramTests
maxK: 5_000_000UL), trackAllValues: true));
primeField.SetValue(null, new ThreadLocal<PrimeTester>(() => new PrimeTester(), trackAllValues: true));
CandidatesCalculator.OverrideResidueTrackers(new ThreadLocal<ModResidueTracker>(() => new ModResidueTracker(ResidueModel.Identity, 2UL, true), trackAllValues: true));
forceCpuProp!.SetValue(null, false);
try
{
@@ -306,6 +330,7 @@ public class ProgramTests
mersenneField.SetValue(null, null);
primeField.SetValue(null, null);
CandidatesCalculator.ResetResidueTrackers();
forceCpuProp!.SetValue(null, false);
ResetCliArguments();
}
}
@@ -317,6 +342,7 @@ public class ProgramTests
var mersenneField = typeof(Program).GetField("MersenneTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var primeField = typeof(Program).GetField("PrimeTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var forceCpuProp = typeof(GpuContextPool).GetProperty("ForceCpu");
mersenneField.SetValue(null, new ThreadLocal<MersenneNumberTester>(() => new MersenneNumberTester(
useIncremental: true,
@@ -324,6 +350,7 @@ public class ProgramTests
maxK: 5_000_000UL), trackAllValues: true));
primeField.SetValue(null, new ThreadLocal<PrimeTester>(() => new PrimeTester(), trackAllValues: true));
CandidatesCalculator.OverrideResidueTrackers(new ThreadLocal<ModResidueTracker>(() => new ModResidueTracker(ResidueModel.Identity, 2UL, true), trackAllValues: true));
forceCpuProp!.SetValue(null, false);
try
{
@@ -340,6 +367,7 @@ public class ProgramTests
mersenneField.SetValue(null, null);
primeField.SetValue(null, null);
CandidatesCalculator.ResetResidueTrackers();
forceCpuProp!.SetValue(null, false);
ResetCliArguments();
}
}
@@ -352,6 +380,7 @@ public class ProgramTests
var mersenneField = typeof(Program).GetField("MersenneTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var primeField = typeof(Program).GetField("PrimeTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var forceCpuProp = typeof(GpuContextPool).GetProperty("ForceCpu");
mersenneField.SetValue(null, new ThreadLocal<MersenneNumberTester>(() => new MersenneNumberTester(
useIncremental: true,
@@ -361,6 +390,7 @@ public class ProgramTests
maxK: 1_024UL), trackAllValues: true));
primeField.SetValue(null, new ThreadLocal<PrimeTester>(() => new PrimeTester(), trackAllValues: true));
CandidatesCalculator.OverrideResidueTrackers(new ThreadLocal<ModResidueTracker>(() => new ModResidueTracker(ResidueModel.Identity, exponent, true), trackAllValues: true));
forceCpuProp!.SetValue(null, true);
try
{
@@ -372,6 +402,7 @@ public class ProgramTests
mersenneField.SetValue(null, null);
primeField.SetValue(null, null);
CandidatesCalculator.ResetResidueTrackers();
forceCpuProp!.SetValue(null, false);
ResetCliArguments();
}
}
@@ -386,6 +417,7 @@ public class ProgramTests
var mersenneField = typeof(Program).GetField("MersenneTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var primeField = typeof(Program).GetField("PrimeTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var forceCpuProp = typeof(GpuContextPool).GetProperty("ForceCpu");
mersenneField.SetValue(null, new ThreadLocal<MersenneNumberTester>(() => new MersenneNumberTester(
useIncremental: false,
@@ -396,6 +428,7 @@ public class ProgramTests
maxK: configuration.ResidueMaxK), trackAllValues: true));
primeField.SetValue(null, new ThreadLocal<PrimeTester>(() => new PrimeTester(), trackAllValues: true));
CandidatesCalculator.OverrideResidueTrackers(new ThreadLocal<ModResidueTracker>(() => new ModResidueTracker(ResidueModel.Identity, exponent, true), trackAllValues: true));
forceCpuProp!.SetValue(null, false);
try
{
@@ -407,7 +440,9 @@ public class ProgramTests
mersenneField.SetValue(null, null);
primeField.SetValue(null, null);
CandidatesCalculator.ResetResidueTrackers();
forceCpuProp!.SetValue(null, false);
ResetCliArguments();
GpuContextPool.DisposeAll();
}
}
@@ -471,10 +506,12 @@ public class ProgramTests
var mersenneField = typeof(Program).GetField("MersenneTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var primeField = typeof(Program).GetField("PrimeTesters", BindingFlags.NonPublic | BindingFlags.Static)!;
var compositeField = typeof(Program).GetField("_lastCompositeP", BindingFlags.NonPublic | BindingFlags.Static)!;
var forceCpuProp = typeof(GpuContextPool).GetProperty("ForceCpu");
mersenneField.SetValue(null, new ThreadLocal<MersenneNumberTester>(() => new MersenneNumberTester(useIncremental: true, useResidue: false, maxK: 1_000UL), trackAllValues: true));
primeField.SetValue(null, new ThreadLocal<PrimeTester>(() => new PrimeTester(), trackAllValues: true));
CandidatesCalculator.OverrideResidueTrackers(new ThreadLocal<ModResidueTracker>(() => new ModResidueTracker(ResidueModel.Identity, 2UL, true), trackAllValues: true));
forceCpuProp!.SetValue(null, true);
try
{
@@ -495,6 +532,7 @@ public class ProgramTests
primeField.SetValue(null, null);
CandidatesCalculator.ResetResidueTrackers();
compositeField.SetValue(null, false);
forceCpuProp!.SetValue(null, false);
ResetCliArguments();
}
}
@@ -1,3 +1,6 @@
using System.Collections.Generic;
using System.IO;
using System.Numerics;
using FluentAssertions;
using PerfectNumbers.Core;
using PerfectNumbers.Core.Gpu;
@@ -1,13 +1,15 @@
using System.Buffers.Text;
using System.IO;
using System.Runtime.CompilerServices;
using System.Text;
using System.Threading;
using PerfectNumbers.Core;
namespace EvenPerfectBitScanner;
internal static class CalculationResultHandler
{
private const string ResultsHeader = "p,divisor,searchedMersenne,detailedCheck,passedAllTests";
private const string ResultsHeader = "p,searchedMersenne,detailedCheck,passedAllTests";
private const string PrimeFoundSuffix = " (FOUND VALID CANDIDATES)";
internal const int DefaultWriteBatchSize = 100;
@@ -93,19 +95,19 @@ internal static class CalculationResultHandler
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static void HandleResult(ulong currentP, ulong divisor, bool searchedMersenne, bool detailedCheck, bool passedAllTests, bool lastWasComposite)
internal static void HandleResult(ulong currentP, bool searchedMersenne, bool detailedCheck, bool passedAllTests, bool lastWasComposite)
{
// Program flow ensures Initialize(...) and InitializeOutputBuffer() ran before this call. Do not add initialization guards here.
Span<byte> stackBuffer = stackalloc byte[128];
byte[]? rentedBuffer = null;
Span<byte> utf8Span = stackBuffer;
int byteCount = TryFormatResultLine(utf8Span, currentP, divisor, searchedMersenne, detailedCheck, passedAllTests);
int byteCount = TryFormatResultLine(utf8Span, currentP, searchedMersenne, detailedCheck, passedAllTests);
if (byteCount < 0)
{
rentedBuffer = ThreadStaticPools.BytePool.Rent(256);
utf8Span = rentedBuffer;
byteCount = TryFormatResultLine(utf8Span, currentP, divisor, searchedMersenne, detailedCheck, passedAllTests);
byteCount = TryFormatResultLine(utf8Span, currentP, searchedMersenne, detailedCheck, passedAllTests);
if (byteCount < 0)
{
ThreadStaticPools.BytePool.Return(rentedBuffer);
@@ -229,7 +231,7 @@ internal static class CalculationResultHandler
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static int TryFormatResultLine(Span<byte> destination, ulong currentP, ulong divisor, bool searchedMersenne, bool detailedCheck, bool passedAllTests)
private static int TryFormatResultLine(Span<byte> destination, ulong currentP, bool searchedMersenne, bool detailedCheck, bool passedAllTests)
{
int offset = 0;
@@ -246,19 +248,6 @@ internal static class CalculationResultHandler
destination[offset++] = (byte)',';
if (!Utf8Formatter.TryFormat(divisor, destination[offset..], out written))
{
return -1;
}
offset += written;
if (offset >= destination.Length)
{
return -1;
}
destination[offset++] = (byte)',';
if (!Utf8Formatter.TryFormat(searchedMersenne, destination[offset..], out written))
{
return -1;
@@ -1,4 +1,5 @@
using System.Globalization;
using System.IO;
namespace EvenPerfectBitScanner.Candidates;
@@ -1,4 +1,5 @@
using System.Runtime.CompilerServices;
using System.Threading;
using Open.Numeric.Primes;
using PerfectNumbers.Core;
using EvenPerfectBitScanner.Candidates.Transforms;
@@ -1,4 +1,6 @@
using System.Runtime.CompilerServices;
using System.Threading;
using EvenPerfectBitScanner.Candidates;
using Open.Numeric.Primes;
namespace EvenPerfectBitScanner.Candidates.Transforms;
@@ -1,4 +1,6 @@
using System.Runtime.CompilerServices;
using System.Threading;
using EvenPerfectBitScanner.Candidates;
namespace EvenPerfectBitScanner.Candidates.Transforms;
@@ -1,4 +1,5 @@
using System.Runtime.CompilerServices;
using System.Threading;
namespace EvenPerfectBitScanner.Candidates.Transforms;
+2
View File
@@ -1,4 +1,6 @@
using System;
using System.Globalization;
using System.Numerics;
using PerfectNumbers.Core;
using PerfectNumbers.Core.Gpu;
@@ -1,6 +1,7 @@
using Open.Collections;
using PerfectNumbers.Core;
using PerfectNumbers.Core.Gpu;
using EvenPerfectBitScanner;
namespace EvenPerfectBitScanner.IO;
@@ -100,7 +101,6 @@ internal static class CalculationResultsFile
int first = 0;
int second = 0;
int third = 0;
int fourth = 0;
ulong parsedP = 0UL;
ReadOnlySpan<char> detailedSpan = default;
ReadOnlySpan<char> passedAllTestsSpan = default;
@@ -140,15 +140,8 @@ internal static class CalculationResultsFile
continue;
}
span = span[(third + 1)..];
fourth = span.IndexOf(',');
if (fourth < 0)
{
continue;
}
detailedSpan = span[..fourth];
passedAllTestsSpan = span[(fourth + 1)..];
detailedSpan = span[..third];
passedAllTestsSpan = span[(third + 1)..];
if (Utf8CliParser.TryParseBoolean(detailedSpan, out detailed) && Utf8CliParser.TryParseBoolean(passedAllTestsSpan, out passedAllTests))
{
+13 -13
View File
@@ -12,7 +12,7 @@ namespace EvenPerfectBitScanner;
internal static class Program
{
// private static ThreadLocal<PrimeTester> PrimeTesters = null!;
private static ThreadLocal<PrimeTester> PrimeTesters = null!;
private static ThreadLocal<MersenneNumberTester> MersenneTesters = null!;
private const ulong InitialP = PerfectNumberConstants.BiggestKnownEvenPerfectP;
private static MersenneNumberDivisorGpuTester? _divisorTester;
@@ -58,17 +58,14 @@ internal static class Program
bool startPrimeProvided = _cliArguments.StartPrimeProvided;
int threadCount = Math.Max(1, _cliArguments.ThreadCount);
int gpuPrimeBatch = Math.Max(1, _cliArguments.GpuPrimeBatch);
// int gpuPrimeThreads = SharedGpuContext.Device.MaxNumThreads;
int gpuPrimeThreads = Math.Max(1, _cliArguments.GpuPrimeThreads);
UnboundedTaskScheduler.ConfigureThreadCount(threadCount);
PrimeTester.GpuBatchSize = gpuPrimeBatch;
GpuPrimeWorkLimiter.SetLimit(gpuPrimeThreads);
Console.WriteLine("Warming up GPU kernels");
PrimeTester.WarmUpGpuKernels(1024);
// PrimeTester.WarmUpGpuKernels(gpuPrimeThreads >> 4);
GpuContextPool.WarmUpPool(threadCount);
PrimeTester.WarmUpGpuKernels(threadCount);
Console.WriteLine("Starting up threads...");
_ = UnboundedTaskScheduler.Instance;
int blockSize = Math.Max(1, _cliArguments.BlockSize);
int gpuPrimeThreads = Math.Max(1, _cliArguments.GpuPrimeThreads);
GpuKernelType kernelType = _cliArguments.KernelType;
bool useBitTransform = _cliArguments.UseBitTransform;
bool useOrder = _cliArguments.UseOrder;
@@ -120,6 +117,9 @@ internal static class Program
return;
}
// Apply GPU prime sieve runtime configuration
GpuPrimeWorkLimiter.SetLimit(gpuPrimeThreads);
PrimeTester.GpuBatchSize = gpuPrimeBatch;
MersenneDivisorCycles mersenneDivisorCycles = new();
if (!File.Exists(cyclesPath) || continueCyclesGeneration)
@@ -178,7 +178,7 @@ internal static class Program
blockSize = useByDivisor ? 1 : blockSize;
CandidatesCalculator.Initialize(currentP);
// PrimeTesters = new ThreadLocal<PrimeTester>(() => new PrimeTester(), trackAllValues: true);
PrimeTesters = new ThreadLocal<PrimeTester>(() => new PrimeTester(), trackAllValues: true);
// Note: --primes-device controls default device for library kernels; p primality remains CPU here.
// Initialize per-thread p residue tracker (Identity model) at currentP
if (!useDivisor && !_cliArguments.UseByDivisor)
@@ -422,7 +422,7 @@ internal static class Program
_byDivisorStartPrime,
static () => _lastCompositeP = true,
static () => _lastCompositeP = false,
static (candidate, searchedMersenne, detailedCheck, passedAllTests, divisor) => CalculationResultHandler.HandleResult(candidate, divisor, searchedMersenne, detailedCheck, passedAllTests, _lastCompositeP),
static (candidate, searchedMersenne, detailedCheck, passedAllTests) => CalculationResultHandler.HandleResult(candidate, searchedMersenne, detailedCheck, passedAllTests, _lastCompositeP),
threadCount,
byDivisorPrimeRange);
@@ -483,7 +483,7 @@ internal static class Program
{
p = buffer[j];
passedAllTests = IsEvenPerfectCandidate(p, divisorCyclesSearchLimit, out searchedMersenne, out detailedCheck);
CalculationResultHandler.HandleResult(p, 0UL, searchedMersenne, detailedCheck, passedAllTests, _lastCompositeP);
CalculationResultHandler.HandleResult(p, searchedMersenne, detailedCheck, passedAllTests, _lastCompositeP);
}
continue;
@@ -506,7 +506,7 @@ internal static class Program
}
passedAllTests = IsEvenPerfectCandidate(p, divisorCyclesSearchLimit, out searchedMersenne, out detailedCheck);
CalculationResultHandler.HandleResult(p, 0UL, searchedMersenne, detailedCheck, passedAllTests, _lastCompositeP);
CalculationResultHandler.HandleResult(p, searchedMersenne, detailedCheck, passedAllTests, _lastCompositeP);
if (p == maxP)
{
@@ -628,7 +628,7 @@ internal static class Program
{
if (!(_runPrimesOnCpu
? PrimeTester.IsPrime(p)
: HeuristicCombinedPrimeTester.IsPrimeGpu(p)))
: PrimeTesters.Value!.IsPrimeGpu(p)))
{
_lastCompositeP = true;
return false;
@@ -649,7 +649,7 @@ internal static class Program
if (_cliArguments.UseByDivisor)
{
// Windowed pow2mod kernel handles by-divisor scans.
return _byDivisorTester!.IsPrime(p, out detailedCheck, out _);
return _byDivisorTester!.IsPrime(p, out detailedCheck);
}
detailedCheck = MersenneTesters.Value!.IsMersennePrime(p);
+1
View File
@@ -1,3 +1,4 @@
using System;
using System.Buffers;
using System.Buffers.Text;
using System.Text;
@@ -1,3 +1,7 @@
using FluentAssertions;
using ILGPU;
using ILGPU.Runtime;
using PerfectNumbers.Core.Gpu;
using Xunit;
namespace PerfectNumbers.Core.Tests.Gpu;
@@ -1,8 +1,8 @@
using System.Reflection;
using FluentAssertions;
using ILGPU;
using ILGPU.Runtime;
using PerfectNumbers.Core.Gpu;
using PerfectNumbers.Core.Gpu.Accelerators;
using Xunit;
namespace PerfectNumbers.Core.Tests.Gpu;
@@ -114,10 +114,14 @@ public class GpuKernelCompilationTests
typeof(PrimeOrderGpuHeuristics).GetMethod("GetPow2ModKernel", BindingFlags.NonPublic | BindingFlags.Static)
?? throw new InvalidOperationException("PrimeOrderGpuHeuristics.GetPow2ModKernel not found.");
private static readonly MethodInfo PrimeOrderGetPow2ModWideKernelMethod =
typeof(PrimeOrderGpuHeuristics).GetMethod("GetPow2ModWideKernel", BindingFlags.NonPublic | BindingFlags.Static)
?? throw new InvalidOperationException("PrimeOrderGpuHeuristics.GetPow2ModWideKernel not found.");
private static readonly Action<Index1D, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>> MersenneDivisorCyclesKernel =
DivisorCycleKernels.GpuDivisorCycleKernel;
private static readonly Action<Index1D, ArrayView<ulong>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<byte>> PrimeTesterSmallPrimeKernel =
private static readonly Action<Index1D, ArrayView<ulong>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<byte>> PrimeTesterSmallPrimeKernel =
PrimeTesterKernels.SmallPrimeSieveKernel;
private static readonly Action<Index1D, ArrayView<ulong>, ArrayView<byte>> PrimeTesterSharesFactorKernel =
@@ -321,67 +325,56 @@ public class GpuKernelCompilationTests
private static void CompilePrimeOrderPow2ModWideKernel(Accelerator accelerator)
{
var kernel = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView1D<GpuUInt128, Stride1D.Dense>, GpuUInt128, ArrayView1D<GpuUInt128, Stride1D.Dense>>(PrimeOrderGpuHeuristics.Pow2ModKernelWide);
_ = kernel;
_ = PrimeOrderGetPow2ModWideKernelMethod.Invoke(null, new object[] { accelerator });
}
private static void CompileMersenneDivisorCyclesKernel(Accelerator accelerator)
{
var kernel = accelerator.LoadAutoGroupedStreamKernel(MersenneDivisorCyclesKernel);
var kernel = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>(MersenneDivisorCyclesKernel);
_ = kernel;
}
private static void CompilePrimeTesterSmallPrimeKernel(Accelerator accelerator)
{
var kernel = accelerator.LoadAutoGroupedStreamKernel(PrimeTesterSmallPrimeKernel);
var kernel = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<ulong>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<byte>>(PrimeTesterSmallPrimeKernel);
_ = kernel;
}
private static void CompilePrimeTesterSharesFactorKernel(Accelerator accelerator)
{
var kernel = accelerator.LoadAutoGroupedStreamKernel(PrimeTesterSharesFactorKernel);
var kernel = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<ulong>, ArrayView<byte>>(PrimeTesterSharesFactorKernel);
_ = kernel;
}
private static KernelType _kernelType = KernelType.Pow2ModKernelScan | KernelType.OrderKernelScan | KernelType.IncrementalKernelScan | KernelType.IncrementalOrderKernelScan | KernelType.Pow2ModOrderKernelScan;
private static void CompileGpuKernelPoolKernels(Accelerator accelerator)
{
private static void CompileGpuKernelPoolKernels(Accelerator accelerator)
{
_ = accelerator;
var lease = GpuKernelPool.GetKernel(useGpuOrder: false);
try
{
_ = lease.OrderKernel;
_ = lease.IncrementalKernel;
_ = lease.Pow2ModKernel;
_ = lease.IncrementalOrderKernel;
_ = lease.Pow2ModOrderKernel;
}
finally
{
lease.Dispose();
}
GpuPrimeWorkLimiter.Acquire();
int acceleratorIndex = AcceleratorPool.Shared.Rent();
AcceleratorStream stream = AcceleratorStreamPool.Rent(acceleratorIndex);
try
{
var kernels = GpuKernelPool.GetOrAddKernels(acceleratorIndex, stream, _kernelType);
_ = kernels.Order;
_ = kernels.Incremental;
_ = kernels.Pow2Mod;
_ = kernels.IncrementalOrder;
_ = kernels.Pow2ModOrder;
}
finally
{
stream.Synchronize();
AcceleratorStreamPool.Return(acceleratorIndex, stream);
// GpuPrimeWorkLimiter.Release();
}
stream = AcceleratorStreamPool.Rent(acceleratorIndex);
GpuPrimeWorkLimiter.Acquire();
try
{
var kernels = GpuKernelPool.GetOrAddKernels(acceleratorIndex, stream, _kernelType);
_ = kernels.Order;
_ = kernels.Incremental;
_ = kernels.Pow2Mod;
_ = kernels.IncrementalOrder;
_ = kernels.Pow2ModOrder;
}
finally
{
stream.Synchronize();
AcceleratorStreamPool.Return(acceleratorIndex, stream);
// GpuPrimeWorkLimiter.Release();
}
}
var orderLease = GpuKernelPool.GetKernel(useGpuOrder: true);
try
{
_ = orderLease.OrderKernel;
_ = orderLease.IncrementalKernel;
_ = orderLease.Pow2ModKernel;
_ = orderLease.IncrementalOrderKernel;
_ = orderLease.Pow2ModOrderKernel;
}
finally
{
orderLease.Dispose();
}
}
}
@@ -18,19 +18,19 @@ public class GpuPrimeLimiterTests
var startedSecond = new TaskCompletionSource<bool>();
var sw = new Stopwatch();
GpuPrimeWorkLimiter.Acquire();
var first = GpuPrimeWorkLimiter.Acquire();
sw.Start();
var secondTask = Task.Run(() =>
{
GpuPrimeWorkLimiter.Acquire();
var second = GpuPrimeWorkLimiter.Acquire();
try
{
startedSecond.TrySetResult(true);
}
finally
{
GpuPrimeWorkLimiter.Release();
second.Dispose();
}
});
@@ -43,7 +43,7 @@ public class GpuPrimeLimiterTests
finally
{
// Release first after the initial wait so the second task can proceed.
GpuPrimeWorkLimiter.Release();
first.Dispose();
}
await secondTask.WaitAsync(TimeSpan.FromSeconds(1));
+343 -328
View File
@@ -13,352 +13,367 @@ namespace PerfectNumbers.Core.Tests.Gpu;
[Collection("GpuNtt")]
public class NttGpuMathTests
{
[Fact]
[Trait("Category", "Fast")]
public void ForwardGpu_reference_matches_cpu_forward()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Reference;
Span<GpuUInt128> cpu = stackalloc GpuUInt128[4];
cpu[0] = new GpuUInt128(0UL, 1UL);
cpu[1] = new GpuUInt128(0UL, 2UL);
cpu[2] = new GpuUInt128(0UL, 3UL);
cpu[3] = new GpuUInt128(0UL, 4UL);
Span<GpuUInt128> gpu = stackalloc GpuUInt128[4];
cpu.CopyTo(gpu);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
NttGpuMath.Forward(cpu, modulus, primitiveRoot);
NttGpuMath.ForwardGpu(gpu, modulus, primitiveRoot);
for (int i = 0; i < cpu.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void ForwardGpu_reference_matches_cpu_forward()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Reference;
Span<GpuUInt128> cpu = stackalloc GpuUInt128[4];
cpu[0] = new GpuUInt128(0UL, 1UL);
cpu[1] = new GpuUInt128(0UL, 2UL);
cpu[2] = new GpuUInt128(0UL, 3UL);
cpu[3] = new GpuUInt128(0UL, 4UL);
Span<GpuUInt128> gpu = stackalloc GpuUInt128[4];
cpu.CopyTo(gpu);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
NttGpuMath.Forward(cpu, modulus, primitiveRoot);
NttGpuMath.ForwardGpu(gpu, modulus, primitiveRoot);
for (int i = 0; i < cpu.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void ForwardGpu_staged_matches_cpu_forward()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Staged;
Span<GpuUInt128> cpu = stackalloc GpuUInt128[4];
cpu[0] = new GpuUInt128(0UL, 1UL);
cpu[1] = new GpuUInt128(0UL, 2UL);
cpu[2] = new GpuUInt128(0UL, 3UL);
cpu[3] = new GpuUInt128(0UL, 4UL);
Span<GpuUInt128> gpu = stackalloc GpuUInt128[4];
cpu.CopyTo(gpu);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
NttGpuMath.Forward(cpu, modulus, primitiveRoot);
NttGpuMath.ForwardGpu(gpu, modulus, primitiveRoot);
for (int i = 0; i < cpu.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void ForwardGpu_staged_matches_cpu_forward()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Staged;
Span<GpuUInt128> cpu = stackalloc GpuUInt128[4];
cpu[0] = new GpuUInt128(0UL, 1UL);
cpu[1] = new GpuUInt128(0UL, 2UL);
cpu[2] = new GpuUInt128(0UL, 3UL);
cpu[3] = new GpuUInt128(0UL, 4UL);
Span<GpuUInt128> gpu = stackalloc GpuUInt128[4];
cpu.CopyTo(gpu);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
NttGpuMath.Forward(cpu, modulus, primitiveRoot);
NttGpuMath.ForwardGpu(gpu, modulus, primitiveRoot);
for (int i = 0; i < cpu.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void InverseGpu_reference_matches_cpu_inverse()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Reference;
Span<GpuUInt128> input = stackalloc GpuUInt128[4];
input[0] = new GpuUInt128(0UL, 5UL);
input[1] = new GpuUInt128(0UL, 7UL);
input[2] = new GpuUInt128(0UL, 9UL);
input[3] = new GpuUInt128(0UL, 11UL);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
Span<GpuUInt128> transformed = stackalloc GpuUInt128[4];
input.CopyTo(transformed);
NttGpuMath.Forward(transformed, modulus, primitiveRoot);
Span<GpuUInt128> cpu = stackalloc GpuUInt128[4];
transformed.CopyTo(cpu);
NttGpuMath.Inverse(cpu, modulus, primitiveRoot);
Span<GpuUInt128> gpu = stackalloc GpuUInt128[4];
transformed.CopyTo(gpu);
NttGpuMath.InverseGpu(gpu, modulus, primitiveRoot);
for (int i = 0; i < input.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void InverseGpu_reference_matches_cpu_inverse()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Reference;
Span<GpuUInt128> input = stackalloc GpuUInt128[4];
input[0] = new GpuUInt128(0UL, 5UL);
input[1] = new GpuUInt128(0UL, 7UL);
input[2] = new GpuUInt128(0UL, 9UL);
input[3] = new GpuUInt128(0UL, 11UL);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
Span<GpuUInt128> transformed = stackalloc GpuUInt128[4];
input.CopyTo(transformed);
NttGpuMath.Forward(transformed, modulus, primitiveRoot);
Span<GpuUInt128> cpu = stackalloc GpuUInt128[4];
transformed.CopyTo(cpu);
NttGpuMath.Inverse(cpu, modulus, primitiveRoot);
Span<GpuUInt128> gpu = stackalloc GpuUInt128[4];
transformed.CopyTo(gpu);
NttGpuMath.InverseGpu(gpu, modulus, primitiveRoot);
for (int i = 0; i < input.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void InverseGpu_staged_matches_cpu_inverse()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Staged;
Span<GpuUInt128> input = stackalloc GpuUInt128[4];
input[0] = new GpuUInt128(0UL, 5UL);
input[1] = new GpuUInt128(0UL, 7UL);
input[2] = new GpuUInt128(0UL, 9UL);
input[3] = new GpuUInt128(0UL, 11UL);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
Span<GpuUInt128> transformed = stackalloc GpuUInt128[4];
input.CopyTo(transformed);
NttGpuMath.Forward(transformed, modulus, primitiveRoot);
Span<GpuUInt128> cpu = stackalloc GpuUInt128[4];
transformed.CopyTo(cpu);
NttGpuMath.Inverse(cpu, modulus, primitiveRoot);
Span<GpuUInt128> gpu = stackalloc GpuUInt128[4];
transformed.CopyTo(gpu);
NttGpuMath.InverseGpu(gpu, modulus, primitiveRoot);
for (int i = 0; i < input.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void InverseGpu_staged_matches_cpu_inverse()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Staged;
Span<GpuUInt128> input = stackalloc GpuUInt128[4];
input[0] = new GpuUInt128(0UL, 5UL);
input[1] = new GpuUInt128(0UL, 7UL);
input[2] = new GpuUInt128(0UL, 9UL);
input[3] = new GpuUInt128(0UL, 11UL);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
Span<GpuUInt128> transformed = stackalloc GpuUInt128[4];
input.CopyTo(transformed);
NttGpuMath.Forward(transformed, modulus, primitiveRoot);
Span<GpuUInt128> cpu = stackalloc GpuUInt128[4];
transformed.CopyTo(cpu);
NttGpuMath.Inverse(cpu, modulus, primitiveRoot);
Span<GpuUInt128> gpu = stackalloc GpuUInt128[4];
transformed.CopyTo(gpu);
NttGpuMath.InverseGpu(gpu, modulus, primitiveRoot);
for (int i = 0; i < input.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void Montgomery_twiddle_inverses_multiply_to_r2()
{
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
[Fact]
[Trait("Category", "Fast")]
public void Montgomery_twiddle_inverses_multiply_to_r2()
{
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
var accelerator = SharedGpuContext.CreateAccelerator();
var stream = accelerator.CreateStream();
GpuContextPool.GpuContextLease gpu = GpuContextPool.Rent();
try
{
var accelerator = gpu.Accelerator;
var method = typeof(NttGpuMath).GetMethod("GetSquareCache", BindingFlags.NonPublic | BindingFlags.Static);
method.Should().NotBeNull();
var cache = method!.Invoke(null, new object[] { accelerator, 8, modulus, primitiveRoot })!;
var cacheType = cache.GetType();
var method = typeof(NttGpuMath).GetMethod("GetSquareCache", BindingFlags.NonPublic | BindingFlags.Static);
method.Should().NotBeNull();
var cache = method!.Invoke(null, new object[] { accelerator, 8, modulus, primitiveRoot })!;
var cacheType = cache.GetType();
var twiddlesMont = (MemoryBuffer1D<GpuUInt128, Stride1D.Dense>)cacheType.GetProperty("TwiddlesMont")!.GetValue(cache)!;
var twiddlesInvMont = (MemoryBuffer1D<GpuUInt128, Stride1D.Dense>)cacheType.GetProperty("TwiddlesInvMont")!.GetValue(cache)!;
var r2 = (ulong)cacheType.GetProperty("MontR2Mod64")!.GetValue(cache)!;
var mod = (ulong)cacheType.GetProperty("ModulusLow")!.GetValue(cache)!;
var twiddlesMont = (MemoryBuffer1D<GpuUInt128, Stride1D.Dense>)cacheType.GetProperty("TwiddlesMont")!.GetValue(cache)!;
var twiddlesInvMont = (MemoryBuffer1D<GpuUInt128, Stride1D.Dense>)cacheType.GetProperty("TwiddlesInvMont")!.GetValue(cache)!;
var r2 = (ulong)cacheType.GetProperty("MontR2Mod64")!.GetValue(cache)!;
var mod = (ulong)cacheType.GetProperty("ModulusLow")!.GetValue(cache)!;
int count = 7; // length 8 -> 7 twiddles
var forward = new GpuUInt128[count];
var inverse = new GpuUInt128[count];
twiddlesMont.CopyToCPU(stream, forward);
twiddlesInvMont.CopyToCPU(stream, inverse);
stream.Synchronize();
stream.Dispose();
accelerator.Dispose();
int count = 7; // length 8 -> 7 twiddles
var forward = new GpuUInt128[count];
var inverse = new GpuUInt128[count];
twiddlesMont.CopyToCPU(forward);
twiddlesInvMont.CopyToCPU(inverse);
for (int i = 0; i < count; i++)
{
ulong prod = (ulong)((((BigInteger)forward[i].Low) * inverse[i].Low) % mod);
prod.Should().Be(r2);
}
}
for (int i = 0; i < count; i++)
{
ulong prod = (ulong)((((BigInteger)forward[i].Low) * inverse[i].Low) % mod);
prod.Should().Be(r2);
}
}
finally
{
gpu.Dispose();
}
}
[Fact]
[Trait("Category", "Fast")]
public void ConvolveGpu_reference_matches_cpu_convolve()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Reference;
Span<GpuUInt128> leftCpu = stackalloc GpuUInt128[4];
Span<GpuUInt128> rightCpu = stackalloc GpuUInt128[4];
leftCpu[0] = new GpuUInt128(0UL, 1UL);
leftCpu[1] = new GpuUInt128(0UL, 2UL);
leftCpu[2] = new GpuUInt128(0UL, 3UL);
leftCpu[3] = new GpuUInt128(0UL, 4UL);
rightCpu[0] = new GpuUInt128(0UL, 5UL);
rightCpu[1] = new GpuUInt128(0UL, 6UL);
rightCpu[2] = new GpuUInt128(0UL, 7UL);
rightCpu[3] = new GpuUInt128(0UL, 8UL);
Span<GpuUInt128> leftGpu = stackalloc GpuUInt128[4];
Span<GpuUInt128> rightGpu = stackalloc GpuUInt128[4];
leftCpu.CopyTo(leftGpu);
rightCpu.CopyTo(rightGpu);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
NttGpuMath.Convolve(leftCpu, rightCpu, modulus, primitiveRoot);
NttGpuMath.ConvolveGpu(leftGpu, rightGpu, modulus, primitiveRoot);
for (int i = 0; i < leftCpu.Length; i++)
{
leftGpu[i].Should().Be(leftCpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void ConvolveGpu_reference_matches_cpu_convolve()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Reference;
Span<GpuUInt128> leftCpu = stackalloc GpuUInt128[4];
Span<GpuUInt128> rightCpu = stackalloc GpuUInt128[4];
leftCpu[0] = new GpuUInt128(0UL, 1UL);
leftCpu[1] = new GpuUInt128(0UL, 2UL);
leftCpu[2] = new GpuUInt128(0UL, 3UL);
leftCpu[3] = new GpuUInt128(0UL, 4UL);
rightCpu[0] = new GpuUInt128(0UL, 5UL);
rightCpu[1] = new GpuUInt128(0UL, 6UL);
rightCpu[2] = new GpuUInt128(0UL, 7UL);
rightCpu[3] = new GpuUInt128(0UL, 8UL);
Span<GpuUInt128> leftGpu = stackalloc GpuUInt128[4];
Span<GpuUInt128> rightGpu = stackalloc GpuUInt128[4];
leftCpu.CopyTo(leftGpu);
rightCpu.CopyTo(rightGpu);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
NttGpuMath.Convolve(leftCpu, rightCpu, modulus, primitiveRoot);
NttGpuMath.ConvolveGpu(leftGpu, rightGpu, modulus, primitiveRoot);
for (int i = 0; i < leftCpu.Length; i++)
{
leftGpu[i].Should().Be(leftCpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void ConvolveGpu_staged_matches_cpu_convolve()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Staged;
Span<GpuUInt128> leftCpu = stackalloc GpuUInt128[4];
Span<GpuUInt128> rightCpu = stackalloc GpuUInt128[4];
leftCpu[0] = new GpuUInt128(0UL, 1UL);
leftCpu[1] = new GpuUInt128(0UL, 2UL);
leftCpu[2] = new GpuUInt128(0UL, 3UL);
leftCpu[3] = new GpuUInt128(0UL, 4UL);
rightCpu[0] = new GpuUInt128(0UL, 5UL);
rightCpu[1] = new GpuUInt128(0UL, 6UL);
rightCpu[2] = new GpuUInt128(0UL, 7UL);
rightCpu[3] = new GpuUInt128(0UL, 8UL);
Span<GpuUInt128> leftGpu = stackalloc GpuUInt128[4];
Span<GpuUInt128> rightGpu = stackalloc GpuUInt128[4];
leftCpu.CopyTo(leftGpu);
rightCpu.CopyTo(rightGpu);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
NttGpuMath.Convolve(leftCpu, rightCpu, modulus, primitiveRoot);
NttGpuMath.ConvolveGpu(leftGpu, rightGpu, modulus, primitiveRoot);
for (int i = 0; i < leftCpu.Length; i++)
{
leftGpu[i].Should().Be(leftCpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void ConvolveGpu_staged_matches_cpu_convolve()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Staged;
Span<GpuUInt128> leftCpu = stackalloc GpuUInt128[4];
Span<GpuUInt128> rightCpu = stackalloc GpuUInt128[4];
leftCpu[0] = new GpuUInt128(0UL, 1UL);
leftCpu[1] = new GpuUInt128(0UL, 2UL);
leftCpu[2] = new GpuUInt128(0UL, 3UL);
leftCpu[3] = new GpuUInt128(0UL, 4UL);
rightCpu[0] = new GpuUInt128(0UL, 5UL);
rightCpu[1] = new GpuUInt128(0UL, 6UL);
rightCpu[2] = new GpuUInt128(0UL, 7UL);
rightCpu[3] = new GpuUInt128(0UL, 8UL);
Span<GpuUInt128> leftGpu = stackalloc GpuUInt128[4];
Span<GpuUInt128> rightGpu = stackalloc GpuUInt128[4];
leftCpu.CopyTo(leftGpu);
rightCpu.CopyTo(rightGpu);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
NttGpuMath.Convolve(leftCpu, rightCpu, modulus, primitiveRoot);
NttGpuMath.ConvolveGpu(leftGpu, rightGpu, modulus, primitiveRoot);
for (int i = 0; i < leftCpu.Length; i++)
{
leftGpu[i].Should().Be(leftCpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void SquareGpu_reference_matches_cpu_square()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Reference;
Span<GpuUInt128> cpu = stackalloc GpuUInt128[4];
cpu[0] = new GpuUInt128(0UL, 1UL);
cpu[1] = new GpuUInt128(0UL, 2UL);
cpu[2] = new GpuUInt128(0UL, 3UL);
cpu[3] = new GpuUInt128(0UL, 4UL);
Span<GpuUInt128> gpu = stackalloc GpuUInt128[4];
cpu.CopyTo(gpu);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
NttGpuMath.Square(cpu, modulus, primitiveRoot);
NttGpuMath.SquareGpu(gpu, modulus, primitiveRoot);
for (int i = 0; i < cpu.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void SquareGpu_reference_matches_cpu_square()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Reference;
Span<GpuUInt128> cpu = stackalloc GpuUInt128[4];
cpu[0] = new GpuUInt128(0UL, 1UL);
cpu[1] = new GpuUInt128(0UL, 2UL);
cpu[2] = new GpuUInt128(0UL, 3UL);
cpu[3] = new GpuUInt128(0UL, 4UL);
Span<GpuUInt128> gpu = stackalloc GpuUInt128[4];
cpu.CopyTo(gpu);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
NttGpuMath.Square(cpu, modulus, primitiveRoot);
NttGpuMath.SquareGpu(gpu, modulus, primitiveRoot);
for (int i = 0; i < cpu.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void SquareGpu_staged_matches_cpu_square()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Staged;
Span<GpuUInt128> cpu = stackalloc GpuUInt128[4];
cpu[0] = new GpuUInt128(0UL, 1UL);
cpu[1] = new GpuUInt128(0UL, 2UL);
cpu[2] = new GpuUInt128(0UL, 3UL);
cpu[3] = new GpuUInt128(0UL, 4UL);
Span<GpuUInt128> gpu = stackalloc GpuUInt128[4];
cpu.CopyTo(gpu);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
NttGpuMath.Square(cpu, modulus, primitiveRoot);
NttGpuMath.SquareGpu(gpu, modulus, primitiveRoot);
for (int i = 0; i < cpu.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void SquareGpu_staged_matches_cpu_square()
{
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Staged;
Span<GpuUInt128> cpu = stackalloc GpuUInt128[4];
cpu[0] = new GpuUInt128(0UL, 1UL);
cpu[1] = new GpuUInt128(0UL, 2UL);
cpu[2] = new GpuUInt128(0UL, 3UL);
cpu[3] = new GpuUInt128(0UL, 4UL);
Span<GpuUInt128> gpu = stackalloc GpuUInt128[4];
cpu.CopyTo(gpu);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
NttGpuMath.Square(cpu, modulus, primitiveRoot);
NttGpuMath.SquareGpu(gpu, modulus, primitiveRoot);
for (int i = 0; i < cpu.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
[Fact]
[Trait("Category", "Fast")]
public void BitReverseGpu_matches_cpu()
{
GpuUInt128[] cpu = new GpuUInt128[8];
for (ulong i = 0; i < (ulong)cpu.Length; i++)
{
cpu[i] = new GpuUInt128(0UL, i);
}
[Fact]
[Trait("Category", "Fast")]
public void BitReverseGpu_matches_cpu()
{
GpuUInt128[] cpu = new GpuUInt128[8];
for (ulong i = 0; i < (ulong)cpu.Length; i++)
{
cpu[i] = new GpuUInt128(0UL, i);
}
GpuUInt128[] gpu = (GpuUInt128[])cpu.Clone();
NttGpuMath.BitReverse(cpu);
NttGpuMath.BitReverseGpu(gpu);
gpu.Should().Equal(cpu);
}
GpuUInt128[] gpu = (GpuUInt128[])cpu.Clone();
NttGpuMath.BitReverse(cpu);
NttGpuMath.BitReverseGpu(gpu);
gpu.Should().Equal(cpu);
}
[Fact]
[Trait("Category", "Fast")]
public void DisposeAll_clears_ntt_caches()
{
// Ensure the cache starts empty.
NttGpuMath.ClearCaches();
[Fact]
[Trait("Category", "Fast")]
public void DisposeAll_clears_ntt_caches()
{
// Ensure the cache starts empty.
NttGpuMath.ClearCaches();
Span<GpuUInt128> values = stackalloc GpuUInt128[2];
values[0] = new GpuUInt128(0UL, 1UL);
values[1] = new GpuUInt128(0UL, 2UL);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
Accelerator accelerator = SharedGpuContext.CreateAccelerator();
var stream = accelerator.CreateStream();
var buffer = accelerator.Allocate1D<GpuUInt128>(values.Length);
buffer.View.CopyFromCPU(stream, ref values[0], values.Length);
NttGpuMath.SquareDevice(accelerator, stream, buffer.View, modulus, primitiveRoot);
stream.Synchronize();
stream.Dispose();
buffer.Dispose();
accelerator.Dispose();
Span<GpuUInt128> values = stackalloc GpuUInt128[2];
values[0] = new GpuUInt128(0UL, 1UL);
values[1] = new GpuUInt128(0UL, 2UL);
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
GpuContextPool.GpuContextLease gpu = GpuContextPool.Rent();
try
{
var buffer = gpu.Accelerator.Allocate1D<GpuUInt128>(values.Length);
try
{
buffer.View.CopyFromCPU(ref values[0], values.Length);
NttGpuMath.SquareDevice(gpu.Accelerator, buffer.View, modulus, primitiveRoot);
}
finally
{
buffer.Dispose();
}
}
finally
{
gpu.Dispose();
}
// Verify that the square cache now holds entries for the accelerator.
var field = typeof(NttGpuMath).GetField("SquareCache", BindingFlags.NonPublic | BindingFlags.Static)!;
var cacheObj = field.GetValue(null)!;
int count = (int)cacheObj.GetType().GetProperty("Count")!.GetValue(cacheObj)!;
count.Should().BeGreaterThan(0);
// Verify that the square cache now holds entries for the accelerator.
var field = typeof(NttGpuMath).GetField("SquareCache", BindingFlags.NonPublic | BindingFlags.Static)!;
var cacheObj = field.GetValue(null)!;
int count = (int)cacheObj.GetType().GetProperty("Count")!.GetValue(cacheObj)!;
count.Should().BeGreaterThan(0);
count = (int)cacheObj.GetType().GetProperty("Count")!.GetValue(cacheObj)!;
count.Should().Be(0);
}
GpuContextPool.DisposeAll();
count = (int)cacheObj.GetType().GetProperty("Count")!.GetValue(cacheObj)!;
count.Should().Be(0);
}
}
@@ -9,83 +9,86 @@ namespace PerfectNumbers.Core.Tests.Gpu;
[Trait("Category", "Fast")]
public class NttMontgomeryTests
{
[Fact]
[Trait("Category", "Fast")]
public void SquareDevice_montgomery64_matches_cpu_square_on_small_input()
{
// Small 64-bit modulus and tiny input to keep runtime trivial.
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
[Fact]
[Trait("Category", "Fast")]
public void SquareDevice_montgomery64_matches_cpu_square_on_small_input()
{
// Small 64-bit modulus and tiny input to keep runtime trivial.
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
Span<GpuUInt128> cpu = stackalloc GpuUInt128[8];
for (ulong i = 0; i < (ulong)cpu.Length; i++)
{
cpu[(int)i] = new GpuUInt128(0UL, i + 1UL);
}
Span<GpuUInt128> gpu = stackalloc GpuUInt128[16];
cpu.CopyTo(gpu);
for (int i = cpu.Length; i < gpu.Length; i++)
{
gpu[i] = new GpuUInt128(0UL, 0UL);
}
Span<GpuUInt128> cpu = stackalloc GpuUInt128[8];
for (ulong i = 0; i < (ulong)cpu.Length; i++)
{
cpu[(int)i] = new GpuUInt128(0UL, i + 1UL);
}
Span<GpuUInt128> gpu = stackalloc GpuUInt128[16];
cpu.CopyTo(gpu);
for (int i = cpu.Length; i < gpu.Length; i++)
{
gpu[i] = new GpuUInt128(0UL, 0UL);
}
// CPU reference
NttGpuMath.Square(cpu, modulus, primitiveRoot);
// CPU reference
NttGpuMath.Square(cpu, modulus, primitiveRoot);
// Device execution
var accelerator = SharedGpuContext.CreateAccelerator();
var stream = accelerator.CreateStream();
using var buffer = accelerator.Allocate1D<GpuUInt128>(gpu.Length);
buffer.View.CopyFromCPU(stream, ref gpu[0], gpu.Length);
NttGpuMath.SquareDevice(accelerator, stream, buffer.View, modulus, primitiveRoot);
buffer.View.CopyToCPU(stream, ref gpu[0], gpu.Length);
stream.Synchronize();
stream.Dispose();
accelerator.Dispose();
// Device execution
GpuContextPool.GpuContextLease context = GpuContextPool.Rent();
try
{
var accelerator = context.Accelerator;
using var buffer = accelerator.Allocate1D<GpuUInt128>(gpu.Length);
buffer.View.CopyFromCPU(ref gpu[0], gpu.Length);
NttGpuMath.SquareDevice(accelerator, buffer.View, modulus, primitiveRoot);
buffer.View.CopyToCPU(ref gpu[0], gpu.Length);
for (int i = 0; i < cpu.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
for (int i = 0; i < cpu.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
context.Dispose();
}
}
}
[Fact]
[Trait("Category", "Fast")]
public void InverseDevice_montgomery64_matches_cpu_inverse_on_small_input()
{
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
[Fact]
[Trait("Category", "Fast")]
public void InverseDevice_montgomery64_matches_cpu_inverse_on_small_input()
{
var modulus = new GpuUInt128(0UL, 17UL);
var primitiveRoot = new GpuUInt128(0UL, 3UL);
Span<GpuUInt128> input = stackalloc GpuUInt128[8];
for (ulong i = 0; i < (ulong)input.Length; i++)
{
input[(int)i] = new GpuUInt128(0UL, i + 1UL);
}
Span<GpuUInt128> input = stackalloc GpuUInt128[8];
for (ulong i = 0; i < (ulong)input.Length; i++)
{
input[(int)i] = new GpuUInt128(0UL, i + 1UL);
}
Span<GpuUInt128> transformed = stackalloc GpuUInt128[input.Length];
input.CopyTo(transformed);
NttGpuMath.Forward(transformed, modulus, primitiveRoot);
Span<GpuUInt128> transformed = stackalloc GpuUInt128[input.Length];
input.CopyTo(transformed);
NttGpuMath.Forward(transformed, modulus, primitiveRoot);
Span<GpuUInt128> cpu = stackalloc GpuUInt128[input.Length];
transformed.CopyTo(cpu);
NttGpuMath.Inverse(cpu, modulus, primitiveRoot);
Span<GpuUInt128> cpu = stackalloc GpuUInt128[input.Length];
transformed.CopyTo(cpu);
NttGpuMath.Inverse(cpu, modulus, primitiveRoot);
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Staged;
Span<GpuUInt128> gpu = stackalloc GpuUInt128[input.Length];
transformed.CopyTo(gpu);
NttGpuMath.InverseGpu(gpu, modulus, primitiveRoot);
for (int i = 0; i < input.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
var original = NttGpuMath.GpuTransformBackend;
try
{
NttGpuMath.GpuTransformBackend = NttBackend.Staged;
Span<GpuUInt128> gpu = stackalloc GpuUInt128[input.Length];
transformed.CopyTo(gpu);
NttGpuMath.InverseGpu(gpu, modulus, primitiveRoot);
for (int i = 0; i < input.Length; i++)
{
gpu[i].Should().Be(cpu[i]);
}
}
finally
{
NttGpuMath.GpuTransformBackend = original;
}
}
}
@@ -1,4 +1,5 @@
using FluentAssertions;
using PerfectNumbers.Core.Gpu;
using Xunit;
namespace PerfectNumbers.Core.Tests.Gpu;
@@ -9,23 +10,37 @@ public class PrimeTesterGpuTests
[Fact]
public void IsPrimeGpu_accepts_known_primes()
{
var tester = new PrimeTester();
ulong[] primes = [31UL, 61UL, 89UL, 107UL, 127UL, 521UL];
foreach (ulong prime in primes)
{
PrimeTester.IsPrimeGpu(prime).Should().BeTrue();
}
try
{
var tester = new PrimeTester();
ulong[] primes = [31UL, 61UL, 89UL, 107UL, 127UL, 521UL];
foreach (ulong prime in primes)
{
tester.IsPrimeGpu(prime).Should().BeTrue();
}
}
finally
{
GpuContextPool.DisposeAll();
}
}
[Fact]
public void IsPrimeGpu_rejects_composites()
{
var tester = new PrimeTester();
ulong[] composites = [33UL, 39UL, 51UL, 77UL, 91UL];
foreach (ulong composite in composites)
{
PrimeTester.IsPrimeGpu(composite).Should().BeFalse();
}
try
{
var tester = new PrimeTester();
ulong[] composites = [33UL, 39UL, 51UL, 77UL, 91UL];
foreach (ulong composite in composites)
{
tester.IsPrimeGpu(composite).Should().BeFalse();
}
}
finally
{
GpuContextPool.DisposeAll();
}
}
}
@@ -1,4 +1,5 @@
using FluentAssertions;
using PerfectNumbers.Core;
using Xunit;
namespace PerfectNumbers.Core.Tests.Gpu;
@@ -1,3 +1,7 @@
using System;
using System.Numerics;
using System.Collections.Generic;
using PerfectNumbers.Core;
using FluentAssertions;
using Xunit;
@@ -11,7 +11,7 @@ public class MersenneNumberDivisorByDivisorTesterTests
{
var candidates = new List<ulong> { 5UL, 7UL, 11UL, 13UL };
var tester = new FakeTester();
var results = new List<(ulong Prime, bool Searched, bool Detailed, bool Passed, ulong Divisor)>();
var results = new List<(ulong Prime, bool Searched, bool Detailed, bool Passed)>();
int compositeMarks = 0;
int clearedMarks = 0;
@@ -22,7 +22,7 @@ public class MersenneNumberDivisorByDivisorTesterTests
startPrime: 0UL,
markComposite: () => compositeMarks++,
clearComposite: () => clearedMarks++,
printResult: (prime, searched, detailed, passed, divisor) => results.Add((prime, searched, detailed, passed, divisor)),
printResult: (prime, searched, detailed, passed) => results.Add((prime, searched, detailed, passed)),
threadCount: 1,
primesPerTask: 2);
@@ -32,10 +32,10 @@ public class MersenneNumberDivisorByDivisorTesterTests
results.Should().Equal(
new[]
{
(5UL, true, true, true, 0UL),
(7UL, true, true, false, 7UL),
(11UL, true, true, false, 11UL),
(13UL, true, true, true, 0UL),
(5UL, true, true, true),
(7UL, true, true, false),
(11UL, true, true, false),
(13UL, true, true, true),
});
}
@@ -57,23 +57,10 @@ public class MersenneNumberDivisorByDivisorTesterTests
return DivisorLimit;
}
public bool IsPrime(ulong prime, out bool divisorsExhausted, out ulong divisor)
public bool IsPrime(ulong prime, out bool divisorsExhausted)
{
divisorsExhausted = true;
if (prime % 7UL == 0UL)
{
divisor = 7UL;
return false;
}
if (prime % 11UL == 0UL)
{
divisor = 11UL;
return false;
}
divisor = 0UL;
return true;
return prime % 7UL != 0UL && prime % 11UL != 0UL;
}
public IMersenneNumberDivisorByDivisorTester.IDivisorScanSession CreateDivisorSession()
@@ -96,7 +83,7 @@ public class MersenneNumberDivisorByDivisorTesterTests
throw new NotSupportedException();
}
public void Return()
public void Dispose()
{
}
}
@@ -13,17 +13,14 @@ public class MersenneNumberDivisorCpuTesterTests
var tester = new MersenneNumberDivisorByDivisorCpuTester();
tester.ConfigureFromMaxPrime(11UL);
tester.IsPrime(5UL, out bool divisorsExhausted, out ulong divisor).Should().BeTrue();
tester.IsPrime(5UL, out bool divisorsExhausted).Should().BeTrue();
divisorsExhausted.Should().BeTrue();
divisor.Should().Be(0UL);
tester.IsPrime(7UL, out divisorsExhausted, out divisor).Should().BeTrue();
tester.IsPrime(7UL, out divisorsExhausted).Should().BeTrue();
divisorsExhausted.Should().BeTrue();
divisor.Should().Be(0UL);
tester.IsPrime(11UL, out divisorsExhausted, out divisor).Should().BeFalse();
tester.IsPrime(11UL, out divisorsExhausted).Should().BeFalse();
divisorsExhausted.Should().BeTrue();
divisor.Should().BeGreaterThan(0UL);
}
[Fact]
@@ -50,7 +47,7 @@ public class MersenneNumberDivisorCpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
@@ -75,7 +72,7 @@ public class MersenneNumberDivisorCpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
@@ -100,7 +97,7 @@ public class MersenneNumberDivisorCpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
}
@@ -73,17 +73,14 @@ public class MersenneNumberDivisorGpuTesterTests
var tester = new MersenneNumberDivisorByDivisorGpuTester();
tester.ConfigureFromMaxPrime(43UL);
tester.IsPrime(31UL, out bool exhausted, out ulong divisor).Should().BeTrue();
tester.IsPrime(31UL, out bool exhausted).Should().BeTrue();
exhausted.Should().BeTrue();
divisor.Should().Be(0UL);
tester.IsPrime(37UL, out exhausted, out divisor).Should().BeFalse();
tester.IsPrime(37UL, out exhausted).Should().BeFalse();
exhausted.Should().BeTrue();
divisor.Should().BeGreaterThan(0UL);
tester.IsPrime(43UL, out exhausted, out divisor).Should().BeFalse();
tester.IsPrime(43UL, out exhausted).Should().BeFalse();
exhausted.Should().BeTrue();
divisor.Should().BeGreaterThan(0UL);
}
[Fact]
@@ -108,15 +105,12 @@ public class MersenneNumberDivisorGpuTesterTests
var tester = new MersenneNumberDivisorByDivisorGpuTester();
tester.ConfigureFromMaxPrime(41UL);
tester.IsPrime(31UL, out _, out ulong divisor).Should().BeTrue();
divisor.Should().Be(0UL);
tester.IsPrime(37UL, out bool exhausted, out divisor).Should().BeFalse();
tester.IsPrime(31UL, out _).Should().BeTrue();
tester.IsPrime(37UL, out bool exhausted).Should().BeFalse();
exhausted.Should().BeTrue();
divisor.Should().BeGreaterThan(0UL);
tester.IsPrime(41UL, out bool divisorsExhausted, out divisor).Should().BeFalse();
tester.IsPrime(41UL, out bool divisorsExhausted).Should().BeFalse();
divisorsExhausted.Should().BeTrue();
divisor.Should().BeGreaterThan(0UL);
}
@@ -130,16 +124,8 @@ public class MersenneNumberDivisorGpuTesterTests
var tester = new MersenneNumberDivisorByDivisorGpuTester();
tester.ConfigureFromMaxPrime(exponent);
tester.IsPrime(exponent, out bool exhausted, out ulong divisor).Should().Be(expectedPrime);
tester.IsPrime(exponent, out bool exhausted).Should().Be(expectedPrime);
exhausted.Should().BeTrue();
if (expectedPrime)
{
divisor.Should().Be(0UL);
}
else
{
divisor.Should().BeGreaterThan(0UL);
}
}
[Fact]
[Trait("Category", "Fast")]
@@ -152,9 +138,8 @@ public class MersenneNumberDivisorGpuTesterTests
tester.ConfigureFromMaxPrime(43UL);
tester.IsPrime(41UL, out bool divisorsExhausted, out ulong divisor).Should().BeFalse();
tester.IsPrime(41UL, out bool divisorsExhausted).Should().BeFalse();
divisorsExhausted.Should().BeTrue();
divisor.Should().BeGreaterThan(0UL);
}
[Fact]
@@ -176,7 +161,7 @@ public class MersenneNumberDivisorGpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
@@ -204,7 +189,7 @@ public class MersenneNumberDivisorGpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
@@ -232,7 +217,7 @@ public class MersenneNumberDivisorGpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
@@ -261,7 +246,7 @@ public class MersenneNumberDivisorGpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
@@ -290,7 +275,7 @@ public class MersenneNumberDivisorGpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
@@ -324,15 +309,15 @@ public class MersenneNumberDivisorGpuTesterTests
.GetField("_divisorLimit", BindingFlags.NonPublic | BindingFlags.Instance)!
.SetValue(tester, 200UL);
tester.IsPrime(19UL, out bool divisorsExhausted, out ulong divisor).Should().BeTrue();
tester.IsPrime(19UL, out bool divisorsExhausted).Should().BeTrue();
divisorsExhausted.Should().BeTrue();
divisor.Should().Be(0UL);
}
finally
{
tableField.SetValue(cycles, originalTable);
smallCyclesField.SetValue(cycles, originalSmall);
DivisorCycleCache.Shared.RefreshSnapshot();
GpuContextPool.DisposeAll();
}
}
@@ -360,7 +345,7 @@ public class MersenneNumberDivisorGpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
}
@@ -1,4 +1,5 @@
using FluentAssertions;
using PerfectNumbers.Core;
using PerfectNumbers.Core.Cpu;
using Xunit;
using UInt128 = System.UInt128;
@@ -1,4 +1,5 @@
using FluentAssertions;
using PerfectNumbers.Core;
using PerfectNumbers.Core.Gpu;
using Xunit;
using UInt128 = System.UInt128;
@@ -1,4 +1,5 @@
using FluentAssertions;
using PerfectNumbers.Core;
using PerfectNumbers.Core.Cpu;
using Xunit;
using UInt128 = System.UInt128;
@@ -1,5 +1,6 @@
using System.Reflection;
using FluentAssertions;
using PerfectNumbers.Core;
using PerfectNumbers.Core.Gpu;
using Xunit;
using UInt128 = System.UInt128;
@@ -54,6 +55,7 @@ public class MersenneNumberOrderGpuTesterTests
ulong[]? backupSmall = originalSmall is null ? null : (ulong[])originalSmall.Clone();
cycles.LoadFrom(tempPath);
GpuContextPool.DisposeAll();
try
{
@@ -73,6 +75,7 @@ public class MersenneNumberOrderGpuTesterTests
{
tableField.SetValue(cycles, originalTable);
smallCyclesField.SetValue(cycles, backupSmall);
GpuContextPool.DisposeAll();
}
}
finally
@@ -1,4 +1,5 @@
using FluentAssertions;
using PerfectNumbers.Core;
using PerfectNumbers.Core.Cpu;
using Xunit;
using UInt128 = System.UInt128;
@@ -1,4 +1,5 @@
using FluentAssertions;
using PerfectNumbers.Core;
using PerfectNumbers.Core.Gpu;
using Xunit;
using UInt128 = System.UInt128;
@@ -39,7 +39,7 @@ public class PrimeTesterIsPrimeTests
{
var tester = new PrimeTester();
PrimeTester.IsPrimeGpu(n).Should().Be(expected);
tester.IsPrimeGpu(n).Should().Be(expected);
}
[Fact]
@@ -64,7 +64,7 @@ public class PrimeTesterIsPrimeTests
var testers = new ThreadLocal<PrimeTester>(() => new PrimeTester(), trackAllValues: true);
Parallel.For(0, primes.Length, i =>
{
results[i] = PrimeTester.IsPrimeGpu(primes[i]);
results[i] = testers.Value!.IsPrimeGpu(primes[i]);
});
results.Should().AllBeEquivalentTo(true);
@@ -73,7 +73,7 @@ public class PrimeTesterIsPrimeTests
{
foreach (ulong prime in primes)
{
PrimeTester.IsPrimeGpu(prime).Should().BeTrue();
testers.Value!.IsPrimeGpu(prime).Should().BeTrue();
}
});
}
@@ -62,7 +62,7 @@ internal sealed class MersenneCpuDivisorScanSession : IMersenneNumberDivisorByDi
}
}
public void Return()
public void Dispose()
{
ThreadStaticPools.ReturnMersenneCpuDivisorSession(this);
}
@@ -1,510 +1,487 @@
using System.Collections.Generic;
using System.Runtime.CompilerServices;
using PerfectNumbers.Core;
using PerfectNumbers.Core.Gpu;
using PerfectNumbers.Core.Gpu.Accelerators;
namespace PerfectNumbers.Core.Cpu;
public sealed class MersenneNumberDivisorByDivisorCpuTester : IMersenneNumberDivisorByDivisorTester
{
private ulong _divisorLimit;
private int _batchSize = 1_024;
[ThreadStatic]
private static GpuUInt128WorkSet _divisorScanGpuWorkSet;
private struct GpuUInt128WorkSet
{
public GpuUInt128 Step;
public GpuUInt128 Divisor;
public GpuUInt128 Limit;
}
public int BatchSize
{
get => _batchSize;
set => _batchSize = Math.Max(1, value);
}
public void ConfigureFromMaxPrime(ulong maxPrime)
{
_divisorLimit = ComputeDivisorLimitFromMaxPrime(maxPrime);
}
public ulong DivisorLimit
{
[MethodImpl(MethodImplOptions.AggressiveInlining)]
get
{
return _divisorLimit;
}
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ulong GetAllowedMaxDivisor(ulong prime) => ComputeAllowedMaxDivisor(prime, _divisorLimit);
public bool IsPrime(ulong prime, out bool divisorsExhausted, out ulong divisor)
{
ulong allowedMax = ComputeAllowedMaxDivisor(prime, _divisorLimit);
// The CPU by-divisor run always hands us primes with enormous divisor limits, so the fallback below never executes.
// if (allowedMax < 3UL)
// {
// // EvenPerfectBitScanner routes primes below the small-divisor cutoff to the GPU path, so the CPU path still sees
// // trivial candidates during targeted tests. Short-circuit here to keep those runs aligned with the production flow.
// divisorsExhausted = true;
// return true;
// }
bool processedAll;
bool composite = CheckDivisors(
prime,
allowedMax,
out processedAll,
out divisor);
if (composite)
{
divisorsExhausted = true;
return false;
}
divisorsExhausted = processedAll || composite;
divisor = 0UL;
return true;
}
public void PrepareCandidates(in ReadOnlySpan<ulong> primes, Span<ulong> allowedMaxValues)
{
ulong divisorLimit = _divisorLimit;
int length = primes.Length;
for (int index = 0; index < length; index++)
{
allowedMaxValues[index] = ComputeAllowedMaxDivisor(primes[index], divisorLimit);
}
}
public IMersenneNumberDivisorByDivisorTester.IDivisorScanSession CreateDivisorSession()
{
MersenneCpuDivisorScanSession? session = ThreadStaticPools.RentMersenneCpuDivisorSession();
if (session is not null)
{
return session;
}
return new MersenneCpuDivisorScanSession();
}
private bool CheckDivisors(
ulong prime,
ulong allowedMax,
out bool processedAll,
out ulong foundDivisor)
{
foundDivisor = 0UL;
// The EvenPerfectBitScanner feeds primes >= 138,000,000 here, so allowedMax >= 3 in production runs.
// Keeping the guard commented out documents the reasoning for benchmarks and tests.
// if (allowedMax < 3UL)
// {
// return false;
// }
ref GpuUInt128WorkSet workSet = ref _divisorScanGpuWorkSet;
ref GpuUInt128 step = ref workSet.Step;
step.High = 0UL;
step.Low = prime;
step.ShiftLeft(1);
ref GpuUInt128 limit = ref workSet.Limit;
limit.High = 0UL;
limit.Low = allowedMax;
ref GpuUInt128 divisor = ref workSet.Divisor;
divisor.High = step.High;
divisor.Low = step.Low;
divisor.Add(1UL);
if (divisor.CompareTo(limit) > 0)
{
processedAll = true;
foundDivisor = 0UL;
return false;
}
// Intentionally recomputes factorizations without a per-thread cache.
// The previous factor cache recorded virtually no hits and only slowed down the scan.
_ = DivisorCycleCache.Shared;
ulong stepHigh = step.High;
ulong stepLow = step.Low;
ulong limitHigh = limit.High;
ulong divisorLow = divisor.Low;
// Keep the divisibility filters aligned with the divisor-cycle generator so the
// CPU path never requests cycles that were skipped during cache creation.
LastDigit lastDigit = (prime & 3UL) == 3UL ? LastDigit.Seven : LastDigit.One;
ushort decimalMask = DivisorGenerator.GetDecimalMask(lastDigit);
byte step10;
byte step8;
byte step3;
byte step7;
byte step11;
byte remainder10;
byte remainder8;
byte remainder3;
byte remainder7;
byte remainder11;
if (stepHigh == 0UL && limitHigh == 0UL)
{
step10 = (byte)(stepLow % 10UL);
step8 = (byte)(stepLow & 7UL);
step3 = (byte)(stepLow % 3UL);
step7 = (byte)(stepLow % 7UL);
step11 = (byte)(stepLow % 11UL);
remainder10 = (byte)(divisorLow % 10UL);
remainder8 = (byte)(divisorLow & 7UL);
remainder3 = (byte)(divisorLow % 3UL);
remainder7 = (byte)(divisorLow % 7UL);
remainder11 = (byte)(divisorLow % 11UL);
return CheckDivisors64(
prime,
stepLow,
limit.Low,
divisorLow,
decimalMask,
step10,
step8,
step3,
step7,
step11,
remainder10,
remainder8,
remainder3,
remainder7,
remainder11,
out processedAll,
out foundDivisor);
}
ulong divisorHigh = divisor.High;
step10 = (byte)((((stepHigh % 10UL) * 6UL) + (stepLow % 10UL)) % 10UL);
step8 = (byte)(stepLow % 8UL);
step3 = (byte)(((stepHigh % 3UL) + (stepLow % 3UL)) % 3UL);
step7 = (byte)((((stepHigh % 7UL) * 2UL) + (stepLow % 7UL)) % 7UL);
step11 = (byte)((((stepHigh % 11UL) * 5UL) + (stepLow % 11UL)) % 11UL);
remainder10 = (byte)((((divisorHigh % 10UL) * 6UL) + (divisorLow % 10UL)) % 10UL);
remainder8 = (byte)(divisorLow % 8UL);
remainder3 = (byte)(((divisorHigh % 3UL) + (divisorLow % 3UL)) % 3UL);
remainder7 = (byte)((((divisorHigh % 7UL) * 2UL) + (divisorLow % 7UL)) % 7UL);
remainder11 = (byte)((((divisorHigh % 11UL) * 5UL) + (divisorLow % 11UL)) % 11UL);
var gpu = PrimeOrderCalculatorAccelerator.Rent(1);
while (divisor.CompareTo(limit) <= 0)
{
bool passesSmallModuli = remainder3 != 0 && remainder7 != 0 && remainder11 != 0;
if (passesSmallModuli && (remainder8 == 1 || remainder8 == 7) && ((decimalMask >> remainder10) & 1) != 0)
{
ulong candidate = divisor.Low;
MontgomeryDivisorData divisorData = MontgomeryDivisorData.FromModulus(candidate);
ulong divisorCycle;
// Divisors generated from 2 * k * p + 1 exceed the small-cycle snapshot when p >= 138,000,000, so the short path below never runs.
// if (candidate <= PerfectNumberConstants.MaxQForDivisorCycles)
// {
// divisorCycle = cycleCache.GetCycleLength(candidate);
// }
// else
{
if (!MersenneDivisorCycles.TryCalculateCycleLengthForExponentCpu(
gpu,
candidate,
prime,
divisorData,
out ulong computedCycle,
out bool primeOrderFailed) || computedCycle == 0UL)
{
// Divisors produced by 2 * k * p + 1 always exceed PerfectNumberConstants.MaxQForDivisorCycles
// for the exponents scanned here, so skip the unused cache fallback and compute directly.
divisorCycle = MersenneDivisorCycles.CalculateCycleLength(
candidate,
divisorData,
skipPrimeOrderHeuristic: primeOrderFailed);
}
else
{
divisorCycle = computedCycle;
}
}
if (divisorCycle == prime)
{
// A cycle equal to the tested exponent (which is prime in this path) guarantees that the candidate divides
// the corresponding Mersenne number because the order of 2 modulo the divisor is exactly p.
foundDivisor = candidate;
processedAll = true;
PrimeOrderCalculatorAccelerator.Return(gpu);
return true;
}
if (divisorCycle == 0UL)
{
Console.WriteLine($"Divisor cycle was not calculated for {prime}");
}
}
divisor.Add(step);
remainder10 = AddMod10(remainder10, step10);
remainder8 = AddMod8(remainder8, step8);
remainder3 = AddMod3(remainder3, step3);
remainder7 = AddMod7(remainder7, step7);
remainder11 = AddMod11(remainder11, step11);
}
PrimeOrderCalculatorAccelerator.Return(gpu);
processedAll = true;
foundDivisor = 0UL;
return false;
}
private static bool CheckDivisors64(
ulong prime,
ulong step,
ulong limit,
ulong divisor,
ushort decimalMask,
byte step10,
byte step8,
byte step3,
byte step7,
byte step11,
byte remainder10,
byte remainder8,
byte remainder3,
byte remainder7,
byte remainder11,
out bool processedAll,
out ulong foundDivisor)
{
processedAll = false;
foundDivisor = 0UL;
bool canAdvance = step <= limit;
var gpu = PrimeOrderCalculatorAccelerator.Rent(1);
if (!canAdvance)
{
if (divisor <= limit)
{
if (remainder3 != 0 && remainder7 != 0 && remainder11 != 0 && (remainder8 == 1 || remainder8 == 7) && ((decimalMask >> remainder10) & 1) != 0)
{
MontgomeryDivisorData divisorData = MontgomeryDivisorData.FromModulus(divisor);
ulong divisorCycle;
if (!MersenneDivisorCycles.TryCalculateCycleLengthForExponentCpu(
gpu,
divisor,
prime,
divisorData,
out ulong computedCycle,
out bool primeOrderFailed) || computedCycle == 0UL)
{
divisorCycle = MersenneDivisorCycles.CalculateCycleLength(
divisor,
divisorData,
skipPrimeOrderHeuristic: primeOrderFailed);
}
else
{
divisorCycle = computedCycle;
}
if (divisorCycle == prime)
{
foundDivisor = divisor;
processedAll = true;
PrimeOrderCalculatorAccelerator.Return(gpu);
return true;
}
if (divisorCycle == 0UL)
{
Console.WriteLine($"Divisor cycle was not calculated for {prime}");
}
}
}
processedAll = true;
foundDivisor = 0UL;
return false;
}
if (divisor > limit)
{
processedAll = true;
foundDivisor = 0UL;
return false;
}
ulong remainingIterations = ((limit - divisor) / step) + 1UL;
while (true)
{
bool passesSmallModuli = remainder3 != 0 && remainder7 != 0 && remainder11 != 0;
if (passesSmallModuli && (remainder8 == 1 || remainder8 == 7) && ((decimalMask >> remainder10) & 1) != 0)
{
MontgomeryDivisorData divisorData = MontgomeryDivisorData.FromModulus(divisor);
ulong divisorCycle;
if (!MersenneDivisorCycles.TryCalculateCycleLengthForExponentCpu(
gpu,
divisor,
prime,
divisorData,
out ulong computedCycle,
out bool primeOrderFailed) || computedCycle == 0UL)
{
divisorCycle = MersenneDivisorCycles.CalculateCycleLength(
divisor,
divisorData,
skipPrimeOrderHeuristic: primeOrderFailed);
}
else
{
divisorCycle = computedCycle;
}
if (divisorCycle == prime)
{
foundDivisor = divisor;
processedAll = true;
PrimeOrderCalculatorAccelerator.Return(gpu);
return true;
}
if (divisorCycle == 0UL)
{
Console.WriteLine($"Divisor cycle was not calculated for {prime}");
}
}
remainingIterations--;
if (remainingIterations == 0UL)
{
processedAll = true;
foundDivisor = 0UL;
return false;
}
divisor += step;
remainder10 = AddMod10(remainder10, step10);
remainder8 = AddMod8(remainder8, step8);
remainder3 = AddMod3(remainder3, step3);
remainder7 = AddMod7(remainder7, step7);
remainder11 = AddMod11(remainder11, step11);
}
}
private static byte CheckDivisor(ulong prime, ulong divisorCycle, in MontgomeryDivisorData divisorData)
{
ulong residue = prime.Pow2MontgomeryModWithCycleCpu(divisorCycle, divisorData);
return residue == 1UL ? (byte)1 : (byte)0;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static byte AddMod3(byte value, byte delta)
{
const int Modulus = 3;
int sum = value + delta;
if (sum >= Modulus)
{
sum -= Modulus;
}
return (byte)sum;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static byte AddMod7(byte value, byte delta)
{
const int Modulus = 7;
int sum = value + delta;
if (sum >= Modulus)
{
sum -= Modulus;
}
return (byte)sum;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static byte AddMod10(byte value, byte delta)
{
const int Modulus = 10;
int sum = value + delta;
if (sum >= Modulus)
{
sum -= Modulus;
}
return (byte)sum;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static byte AddMod11(byte value, byte delta)
{
const int Modulus = 11;
int sum = value + delta;
if (sum >= Modulus)
{
sum -= Modulus;
}
return (byte)sum;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static byte AddMod8(byte value, byte delta)
{
return (byte)((value + delta) & 7);
}
private static ulong ComputeDivisorLimitFromMaxPrime(ulong maxPrime)
{
// The by-divisor CPU configuration only supplies primes greater than 1, so the guard below never trips.
// if (maxPrime <= 1UL)
// {
// return 0UL;
// }
if (maxPrime - 1UL >= 64UL)
{
return ulong.MaxValue;
}
return (1UL << (int)(maxPrime - 1UL)) - 1UL;
}
private static ulong ComputeAllowedMaxDivisor(ulong prime, ulong divisorLimit)
{
// Production by-divisor scans only handle primes, so inputs never fall below 2.
// if (prime <= 1UL)
// {
// return 0UL;
// }
if (prime - 1UL >= 64UL)
{
return divisorLimit;
}
return Math.Min((1UL << (int)(prime - 1UL)) - 1UL, divisorLimit);
}
private ulong _divisorLimit;
private int _batchSize = 1_024;
[ThreadStatic]
private static GpuUInt128WorkSet _divisorScanGpuWorkSet;
private struct GpuUInt128WorkSet
{
public GpuUInt128 Step;
public GpuUInt128 Divisor;
public GpuUInt128 Limit;
}
public int BatchSize
{
get => _batchSize;
set => _batchSize = Math.Max(1, value);
}
public void ConfigureFromMaxPrime(ulong maxPrime)
{
_divisorLimit = ComputeDivisorLimitFromMaxPrime(maxPrime);
}
public ulong DivisorLimit
{
[MethodImpl(MethodImplOptions.AggressiveInlining)]
get
{
return _divisorLimit;
}
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ulong GetAllowedMaxDivisor(ulong prime) => ComputeAllowedMaxDivisor(prime, _divisorLimit);
public bool IsPrime(ulong prime, out bool divisorsExhausted)
{
ulong allowedMax = ComputeAllowedMaxDivisor(prime, _divisorLimit);
// The CPU by-divisor run always hands us primes with enormous divisor limits, so the fallback below never executes.
// if (allowedMax < 3UL)
// {
// // EvenPerfectBitScanner routes primes below the small-divisor cutoff to the GPU path, so the CPU path still sees
// // trivial candidates during targeted tests. Short-circuit here to keep those runs aligned with the production flow.
// divisorsExhausted = true;
// return true;
// }
bool processedAll;
bool composite = CheckDivisors(
prime,
allowedMax,
out processedAll);
if (composite)
{
divisorsExhausted = true;
return false;
}
divisorsExhausted = processedAll || composite;
return true;
}
public void PrepareCandidates(in ReadOnlySpan<ulong> primes, Span<ulong> allowedMaxValues)
{
ulong divisorLimit = _divisorLimit;
int length = primes.Length;
for (int index = 0; index < length; index++)
{
allowedMaxValues[index] = ComputeAllowedMaxDivisor(primes[index], divisorLimit);
}
}
public IMersenneNumberDivisorByDivisorTester.IDivisorScanSession CreateDivisorSession()
{
MersenneCpuDivisorScanSession? session = ThreadStaticPools.RentMersenneCpuDivisorSession();
if (session is not null)
{
return session;
}
return new MersenneCpuDivisorScanSession();
}
private bool CheckDivisors(
ulong prime,
ulong allowedMax,
out bool processedAll)
{
processedAll = false;
// The EvenPerfectBitScanner feeds primes >= 138,000,000 here, so allowedMax >= 3 in production runs.
// Keeping the guard commented out documents the reasoning for benchmarks and tests.
// if (allowedMax < 3UL)
// {
// return false;
// }
ref GpuUInt128WorkSet workSet = ref _divisorScanGpuWorkSet;
ref GpuUInt128 step = ref workSet.Step;
step.High = 0UL;
step.Low = prime;
step.ShiftLeft(1);
ref GpuUInt128 limit = ref workSet.Limit;
limit.High = 0UL;
limit.Low = allowedMax;
ref GpuUInt128 divisor = ref workSet.Divisor;
divisor.High = step.High;
divisor.Low = step.Low;
divisor.Add(1UL);
if (divisor.CompareTo(limit) > 0)
{
processedAll = true;
return false;
}
// Intentionally recomputes factorizations without a per-thread cache.
// The previous factor cache recorded virtually no hits and only slowed down the scan.
DivisorCycleCache cycleCache = DivisorCycleCache.Shared;
ulong stepHigh = step.High;
ulong stepLow = step.Low;
ulong limitHigh = limit.High;
ulong divisorLow = divisor.Low;
// Keep the divisibility filters aligned with the divisor-cycle generator so the
// CPU path never requests cycles that were skipped during cache creation.
LastDigit lastDigit = (prime & 3UL) == 3UL ? LastDigit.Seven : LastDigit.One;
ushort decimalMask = DivisorGenerator.GetDecimalMask(lastDigit);
byte step10;
byte step8;
byte step3;
byte step7;
byte step11;
byte remainder10;
byte remainder8;
byte remainder3;
byte remainder7;
byte remainder11;
if (stepHigh == 0UL && limitHigh == 0UL)
{
step10 = (byte)(stepLow % 10UL);
step8 = (byte)(stepLow & 7UL);
step3 = (byte)(stepLow % 3UL);
step7 = (byte)(stepLow % 7UL);
step11 = (byte)(stepLow % 11UL);
remainder10 = (byte)(divisorLow % 10UL);
remainder8 = (byte)(divisorLow & 7UL);
remainder3 = (byte)(divisorLow % 3UL);
remainder7 = (byte)(divisorLow % 7UL);
remainder11 = (byte)(divisorLow % 11UL);
return CheckDivisors64(
prime,
stepLow,
limit.Low,
divisorLow,
decimalMask,
step10,
step8,
step3,
step7,
step11,
remainder10,
remainder8,
remainder3,
remainder7,
remainder11,
out processedAll);
}
ulong divisorHigh = divisor.High;
step10 = (byte)((((stepHigh % 10UL) * 6UL) + (stepLow % 10UL)) % 10UL);
step8 = (byte)(stepLow % 8UL);
step3 = (byte)(((stepHigh % 3UL) + (stepLow % 3UL)) % 3UL);
step7 = (byte)((((stepHigh % 7UL) * 2UL) + (stepLow % 7UL)) % 7UL);
step11 = (byte)((((stepHigh % 11UL) * 5UL) + (stepLow % 11UL)) % 11UL);
remainder10 = (byte)((((divisorHigh % 10UL) * 6UL) + (divisorLow % 10UL)) % 10UL);
remainder8 = (byte)(divisorLow % 8UL);
remainder3 = (byte)(((divisorHigh % 3UL) + (divisorLow % 3UL)) % 3UL);
remainder7 = (byte)((((divisorHigh % 7UL) * 2UL) + (divisorLow % 7UL)) % 7UL);
remainder11 = (byte)((((divisorHigh % 11UL) * 5UL) + (divisorLow % 11UL)) % 11UL);
while (divisor.CompareTo(limit) <= 0)
{
bool passesSmallModuli = remainder3 != 0 && remainder7 != 0 && remainder11 != 0;
if (passesSmallModuli && (remainder8 == 1 || remainder8 == 7) && ((decimalMask >> remainder10) & 1) != 0)
{
ulong candidate = divisor.Low;
MontgomeryDivisorData divisorData = MontgomeryDivisorData.FromModulus(candidate);
ulong divisorCycle;
// Divisors generated from 2 * k * p + 1 exceed the small-cycle snapshot when p >= 138,000,000, so the short path below never runs.
// if (candidate <= PerfectNumberConstants.MaxQForDivisorCycles)
// {
// divisorCycle = cycleCache.GetCycleLength(candidate);
// }
// else
{
if (!MersenneDivisorCycles.TryCalculateCycleLengthForExponentCpu(
candidate,
prime,
divisorData,
out ulong computedCycle,
out bool primeOrderFailed) || computedCycle == 0UL)
{
// Divisors produced by 2 * k * p + 1 always exceed PerfectNumberConstants.MaxQForDivisorCycles
// for the exponents scanned here, so skip the unused cache fallback and compute directly.
divisorCycle = MersenneDivisorCycles.CalculateCycleLength(
candidate,
divisorData,
skipPrimeOrderHeuristic: primeOrderFailed);
}
else
{
divisorCycle = computedCycle;
}
}
if (divisorCycle == prime)
{
// A cycle equal to the tested exponent (which is prime in this path) guarantees that the candidate divides
// the corresponding Mersenne number because the order of 2 modulo the divisor is exactly p.
processedAll = true;
return true;
}
if (divisorCycle == 0UL)
{
Console.WriteLine($"Divisor cycle was not calculated for {prime}");
}
}
divisor.Add(step);
remainder10 = AddMod10(remainder10, step10);
remainder8 = AddMod8(remainder8, step8);
remainder3 = AddMod3(remainder3, step3);
remainder7 = AddMod7(remainder7, step7);
remainder11 = AddMod11(remainder11, step11);
}
processedAll = true;
return false;
}
private static bool CheckDivisors64(
ulong prime,
ulong step,
ulong limit,
ulong divisor,
ushort decimalMask,
byte step10,
byte step8,
byte step3,
byte step7,
byte step11,
byte remainder10,
byte remainder8,
byte remainder3,
byte remainder7,
byte remainder11,
out bool processedAll)
{
processedAll = false;
bool canAdvance = step <= limit;
if (!canAdvance)
{
if (divisor <= limit)
{
if (remainder3 != 0 && remainder7 != 0 && remainder11 != 0 && (remainder8 == 1 || remainder8 == 7) && ((decimalMask >> remainder10) & 1) != 0)
{
MontgomeryDivisorData divisorData = MontgomeryDivisorData.FromModulus(divisor);
ulong divisorCycle;
if (!MersenneDivisorCycles.TryCalculateCycleLengthForExponentCpu(
divisor,
prime,
divisorData,
out ulong computedCycle,
out bool primeOrderFailed) || computedCycle == 0UL)
{
divisorCycle = MersenneDivisorCycles.CalculateCycleLength(
divisor,
divisorData,
skipPrimeOrderHeuristic: primeOrderFailed);
}
else
{
divisorCycle = computedCycle;
}
if (divisorCycle == prime)
{
processedAll = true;
return true;
}
if (divisorCycle == 0UL)
{
Console.WriteLine($"Divisor cycle was not calculated for {prime}");
}
}
}
processedAll = true;
return false;
}
if (divisor > limit)
{
processedAll = true;
return false;
}
ulong remainingIterations = ((limit - divisor) / step) + 1UL;
while (true)
{
bool passesSmallModuli = remainder3 != 0 && remainder7 != 0 && remainder11 != 0;
if (passesSmallModuli && (remainder8 == 1 || remainder8 == 7) && ((decimalMask >> remainder10) & 1) != 0)
{
MontgomeryDivisorData divisorData = MontgomeryDivisorData.FromModulus(divisor);
ulong divisorCycle;
if (!MersenneDivisorCycles.TryCalculateCycleLengthForExponentCpu(
divisor,
prime,
divisorData,
out ulong computedCycle,
out bool primeOrderFailed) || computedCycle == 0UL)
{
divisorCycle = MersenneDivisorCycles.CalculateCycleLength(
divisor,
divisorData,
skipPrimeOrderHeuristic: primeOrderFailed);
}
else
{
divisorCycle = computedCycle;
}
if (divisorCycle == prime)
{
processedAll = true;
return true;
}
if (divisorCycle == 0UL)
{
Console.WriteLine($"Divisor cycle was not calculated for {prime}");
}
}
remainingIterations--;
if (remainingIterations == 0UL)
{
processedAll = true;
return false;
}
divisor += step;
remainder10 = AddMod10(remainder10, step10);
remainder8 = AddMod8(remainder8, step8);
remainder3 = AddMod3(remainder3, step3);
remainder7 = AddMod7(remainder7, step7);
remainder11 = AddMod11(remainder11, step11);
}
}
private static byte CheckDivisor(ulong prime, ulong divisorCycle, in MontgomeryDivisorData divisorData)
{
ulong residue = prime.Pow2MontgomeryModWithCycleCpu(divisorCycle, divisorData);
return residue == 1UL ? (byte)1 : (byte)0;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static byte AddMod3(byte value, byte delta)
{
const int Modulus = 3;
int sum = value + delta;
if (sum >= Modulus)
{
sum -= Modulus;
}
return (byte)sum;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static byte AddMod7(byte value, byte delta)
{
const int Modulus = 7;
int sum = value + delta;
if (sum >= Modulus)
{
sum -= Modulus;
}
return (byte)sum;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static byte AddMod10(byte value, byte delta)
{
const int Modulus = 10;
int sum = value + delta;
if (sum >= Modulus)
{
sum -= Modulus;
}
return (byte)sum;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static byte AddMod11(byte value, byte delta)
{
const int Modulus = 11;
int sum = value + delta;
if (sum >= Modulus)
{
sum -= Modulus;
}
return (byte)sum;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static byte AddMod8(byte value, byte delta)
{
return (byte)((value + delta) & 7);
}
private static ulong ComputeDivisorLimitFromMaxPrime(ulong maxPrime)
{
// The by-divisor CPU configuration only supplies primes greater than 1, so the guard below never trips.
// if (maxPrime <= 1UL)
// {
// return 0UL;
// }
if (maxPrime - 1UL >= 64UL)
{
return ulong.MaxValue;
}
return (1UL << (int)(maxPrime - 1UL)) - 1UL;
}
private static ulong ComputeAllowedMaxDivisor(ulong prime, ulong divisorLimit)
{
// Production by-divisor scans only handle primes, so inputs never fall below 2.
// if (prime <= 1UL)
// {
// return 0UL;
// }
if (prime - 1UL >= 64UL)
{
return divisorLimit;
}
return Math.Min((1UL << (int)(prime - 1UL)) - 1UL, divisorLimit);
}
}
@@ -1,6 +1,6 @@
namespace PerfectNumbers.Core.Cpu;
namespace PerfectNumbers.Core;
internal static class DeterministicRandomCpu
internal static class DeterministicRandom
{
[ThreadStatic]
private static ulong s_threadState;
+267 -315
View File
@@ -1,377 +1,329 @@
using System.Buffers;
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
using ILGPU;
using ILGPU.Runtime;
using PerfectNumbers.Core.Gpu;
using PerfectNumbers.Core.Gpu.Accelerators;
namespace PerfectNumbers.Core;
public sealed class DivisorCycleCache
{
private const byte ByteZero = 0;
private const byte ByteOne = 1;
private const int StackBufferThreshold = 128;
private readonly Accelerator _accelerator;
private readonly int _acceleratorIndex;
private readonly Action<AcceleratorStream, Index1D, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<byte, Stride1D.Dense>> _gpuKernel;
private volatile ulong[] _snapshot;
private volatile bool _useGpuGeneration = true;
private readonly int _divisorCyclesBatchSize;
private static int _sharedDivisorCyclesBatchSize = GpuConstants.GpuCycleStepsPerInvocation;
private const byte ByteZero = 0;
private const byte ByteOne = 1;
private const int StackBufferThreshold = 128;
private const int CycleCacheTrackingLimit = 500_000;
private static readonly HashSet<ulong> CycleCacheTrackedDivisors = new();
private static readonly object CycleCacheTrackingLock = new();
private static ulong CycleCacheHitCount;
private static bool CycleCacheTrackingDisabled;
private readonly ConcurrentDictionary<Accelerator, Action<Index1D, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<byte, Stride1D.Dense>>> _gpuKernelCache = new(AcceleratorReferenceComparer.Instance);
private volatile ulong[] _snapshot;
private volatile bool _useGpuGeneration = true;
private readonly int _divisorCyclesBatchSize;
private static int _sharedDivisorCyclesBatchSize = GpuConstants.GpuCycleStepsPerInvocation;
public static void SetDivisorCyclesBatchSize(int divisorCyclesBatchSize)
{
_sharedDivisorCyclesBatchSize = Math.Max(1, divisorCyclesBatchSize);
}
private const int CycleCacheTrackingLimit = 500_000;
private static readonly HashSet<ulong> CycleCacheTrackedDivisors = new();
private static readonly object CycleCacheTrackingLock = new();
private static ulong CycleCacheHitCount;
private static bool CycleCacheTrackingDisabled;
public static DivisorCycleCache Shared { get; } = new DivisorCycleCache(_sharedDivisorCyclesBatchSize);
public static void SetDivisorCyclesBatchSize(int divisorCyclesBatchSize)
{
_sharedDivisorCyclesBatchSize = Math.Max(1, divisorCyclesBatchSize);
}
public int PreferredBatchSize => _divisorCyclesBatchSize;
public static DivisorCycleCache Shared { get; } = new DivisorCycleCache(_sharedDivisorCyclesBatchSize);
// private static readonly Accelerator[] _accelerators;
public int PreferredBatchSize => _divisorCyclesBatchSize;
private DivisorCycleCache(int divisorCyclesBatchSize)
{
_divisorCyclesBatchSize = Math.Max(1, divisorCyclesBatchSize);
var acceleratorIndex = AcceleratorPool.Shared.Rent();
_acceleratorIndex = acceleratorIndex;
Accelerator accelerator = AcceleratorPool.Shared.Accelerators[acceleratorIndex];
_accelerator = accelerator;
_gpuKernel = LoadKernel(accelerator);
_snapshot = MersenneDivisorCycles.Shared.ExportSmallCyclesSnapshot();
}
private DivisorCycleCache(int divisorCyclesBatchSize)
{
_divisorCyclesBatchSize = Math.Max(1, divisorCyclesBatchSize);
_snapshot = MersenneDivisorCycles.Shared.ExportSmallCyclesSnapshot();
}
public void ConfigureGeneratorDevice(bool useGpu)
{
_useGpuGeneration = useGpu;
}
public void ConfigureGeneratorDevice(bool useGpu)
{
_useGpuGeneration = useGpu;
}
public void RefreshSnapshot()
{
_snapshot = MersenneDivisorCycles.Shared.ExportSmallCyclesSnapshot();
}
public void RefreshSnapshot()
{
_snapshot = MersenneDivisorCycles.Shared.ExportSmallCyclesSnapshot();
}
public ulong GetCycleLength(ulong divisor, bool skipPrimeOrderHeuristic = false)
{
if (!skipPrimeOrderHeuristic)
{
Span<ulong> result = stackalloc ulong[1];
ReadOnlySpan<ulong> singleDivisor = stackalloc ulong[1] { divisor };
GetCycleLengths(singleDivisor, result);
return result[0];
}
public ulong GetCycleLength(ulong divisor, bool skipPrimeOrderHeuristic = false)
{
if (!skipPrimeOrderHeuristic)
{
Span<ulong> result = stackalloc ulong[1];
ReadOnlySpan<ulong> singleDivisor = stackalloc ulong[1] { divisor };
GetCycleLengths(singleDivisor, result);
return result[0];
}
// The skipPrimeOrderHeuristic path is only used for divisors produced by the CPU by-divisor scanner,
// which always generates values greater than one. Keep this guard disabled here to avoid repeating the
// validation already performed by the general GetCycleLengths path.
// if (divisor <= 1UL)
// {
// throw new InvalidDataException("Divisor must be > 1");
// }
// The skipPrimeOrderHeuristic path is only used for divisors produced by the CPU by-divisor scanner,
// which always generates values greater than one. Keep this guard disabled here to avoid repeating the
// validation already performed by the general GetCycleLengths path.
// if (divisor <= 1UL)
// {
// throw new InvalidDataException("Divisor must be > 1");
// }
ulong[] snapshot = _snapshot;
if (divisor < (ulong)snapshot.Length)
{
ulong cached = snapshot[divisor];
if (cached == 0UL)
{
throw new InvalidDataException($"Divisor cycle is missing for {divisor}");
}
ulong[] snapshot = _snapshot;
if (divisor < (ulong)snapshot.Length)
{
ulong cached = snapshot[divisor];
if (cached == 0UL)
{
throw new InvalidDataException($"Divisor cycle is missing for {divisor}");
}
return cached;
}
// ObserveCycleCacheDivisor(divisor);
return cached;
}
MontgomeryDivisorData divisorData = MontgomeryDivisorData.FromModulus(divisor);
return MersenneDivisorCycles.CalculateCycleLength(divisor, divisorData, skipPrimeOrderHeuristic: true);
}
MontgomeryDivisorData divisorData = MontgomeryDivisorData.FromModulus(divisor);
return MersenneDivisorCycles.CalculateCycleLength(divisor, divisorData, skipPrimeOrderHeuristic: true);
}
public void GetCycleLengths(ReadOnlySpan<ulong> divisors, Span<ulong> cycles)
{
ulong[] snapshot = _snapshot;
int length = divisors.Length;
int[]? rentedMissing = null;
Span<int> missingBuffer = length <= StackBufferThreshold
? stackalloc int[length]
: new Span<int>(rentedMissing = ThreadStaticPools.IntPool.Rent(length), 0, length);
public void GetCycleLengths(ReadOnlySpan<ulong> divisors, Span<ulong> cycles)
{
ulong[] snapshot = _snapshot;
int length = divisors.Length;
int[]? rentedMissing = null;
Span<int> missingBuffer = length <= StackBufferThreshold
? stackalloc int[length]
: new Span<int>(rentedMissing = ArrayPool<int>.Shared.Rent(length), 0, length);
int missingCount = 0;
int missingCount = 0;
for (int i = 0; i < length; i++)
{
ulong divisor = divisors[i];
if (divisor <= 1UL)
{
throw new InvalidDataException("Divisor must be > 1");
}
for (int i = 0; i < length; i++)
{
ulong divisor = divisors[i];
if (divisor <= 1UL)
{
throw new InvalidDataException("Divisor must be > 1");
}
if (divisor < (ulong)snapshot.Length)
{
ulong cached = snapshot[divisor];
if (cached == 0UL)
{
throw new InvalidDataException($"Divisor cycle is missing for {divisor}");
}
if (divisor < (ulong)snapshot.Length)
{
ulong cached = snapshot[divisor];
if (cached == 0UL)
{
throw new InvalidDataException($"Divisor cycle is missing for {divisor}");
}
cycles[i] = cached;
}
else
{
missingBuffer[missingCount++] = i;
}
}
// ObserveCycleCacheDivisor(divisor);
cycles[i] = cached;
}
else
{
missingBuffer[missingCount++] = i;
}
}
if (missingCount != 0)
{
ReadOnlySpan<int> missingIndices = missingBuffer[..missingCount];
if (_useGpuGeneration)
{
ComputeCyclesGpu(divisors, cycles, missingIndices);
}
else
{
ComputeCyclesCpu(divisors, cycles, missingIndices);
}
}
if (missingCount != 0)
{
ReadOnlySpan<int> missingIndices = missingBuffer[..missingCount];
if (_useGpuGeneration)
{
ComputeCyclesGpu(divisors, cycles, missingIndices);
}
else
{
ComputeCyclesCpu(divisors, cycles, missingIndices);
}
}
if (rentedMissing is not null)
{
ThreadStaticPools.IntPool.Return(rentedMissing, clearArray: false);
}
}
if (rentedMissing is not null)
{
ArrayPool<int>.Shared.Return(rentedMissing, clearArray: false);
}
}
private static void ObserveCycleCacheDivisor(ulong divisor)
{
bool logHit = false;
ulong hitNumber = 0UL;
bool trackingDisabledNow = false;
private static void ObserveCycleCacheDivisor(ulong divisor)
{
bool logHit = false;
ulong hitNumber = 0UL;
bool trackingDisabledNow = false;
lock (CycleCacheTrackingLock)
{
if (CycleCacheTrackingDisabled)
{
return;
}
lock (CycleCacheTrackingLock)
{
if (CycleCacheTrackingDisabled)
{
return;
}
if (!CycleCacheTrackedDivisors.Add(divisor))
{
CycleCacheHitCount++;
hitNumber = CycleCacheHitCount;
logHit = true;
}
else if (CycleCacheTrackedDivisors.Count >= CycleCacheTrackingLimit)
{
CycleCacheTrackingDisabled = true;
CycleCacheTrackedDivisors.Clear();
trackingDisabledNow = true;
}
}
if (!CycleCacheTrackedDivisors.Add(divisor))
{
CycleCacheHitCount++;
hitNumber = CycleCacheHitCount;
logHit = true;
}
else if (CycleCacheTrackedDivisors.Count >= CycleCacheTrackingLimit)
{
CycleCacheTrackingDisabled = true;
CycleCacheTrackedDivisors.Clear();
trackingDisabledNow = true;
}
}
if (logHit)
{
Console.WriteLine($"Cycle cache hit for divisor {divisor} ({hitNumber})");
}
else if (trackingDisabledNow)
{
Console.WriteLine("Cycle cache hit tracking disabled after exceeding the tracking limit.");
}
}
if (logHit)
{
Console.WriteLine($"Cycle cache hit for divisor {divisor} ({hitNumber})");
}
else if (trackingDisabledNow)
{
Console.WriteLine("Cycle cache hit tracking disabled after exceeding the tracking limit.");
}
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static void ComputeCyclesCpu(ReadOnlySpan<ulong> divisors, Span<ulong> cycles, ReadOnlySpan<int> indices)
{
for (int i = 0; i < indices.Length; i++)
{
int targetIndex = indices[i];
ulong divisor = divisors[targetIndex];
MontgomeryDivisorData divisorData = MontgomeryDivisorData.FromModulus(divisor);
cycles[targetIndex] = MersenneDivisorCycles.CalculateCycleLength(divisor, divisorData);
}
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static void ComputeCyclesCpu(ReadOnlySpan<ulong> divisors, Span<ulong> cycles, ReadOnlySpan<int> indices)
{
for (int i = 0; i < indices.Length; i++)
{
int targetIndex = indices[i];
ulong divisor = divisors[targetIndex];
MontgomeryDivisorData divisorData = MontgomeryDivisorData.FromModulus(divisor);
cycles[targetIndex] = MersenneDivisorCycles.CalculateCycleLength(divisor, divisorData);
}
}
private void ComputeCyclesGpu(ReadOnlySpan<ulong> divisors, Span<ulong> cycles, ReadOnlySpan<int> indices)
{
int count = indices.Length;
ulong[]? rentedDivisors = null;
Span<ulong> workDivisors = count <= StackBufferThreshold
? stackalloc ulong[count]
: new Span<ulong>(rentedDivisors = ThreadStaticPools.UlongPool.Rent(count), 0, count);
private void ComputeCyclesGpu(ReadOnlySpan<ulong> divisors, Span<ulong> cycles, ReadOnlySpan<int> indices)
{
int count = indices.Length;
ulong[]? rentedDivisors = null;
Span<ulong> workDivisors = count <= StackBufferThreshold
? stackalloc ulong[count]
: new Span<ulong>(rentedDivisors = ArrayPool<ulong>.Shared.Rent(count), 0, count);
ulong[]? rentedResults = null;
Span<ulong> workResults = count <= StackBufferThreshold
? stackalloc ulong[count]
: new Span<ulong>(rentedResults = ThreadStaticPools.UlongPool.Rent(count), 0, count);
ulong[]? rentedResults = null;
Span<ulong> workResults = count <= StackBufferThreshold
? stackalloc ulong[count]
: new Span<ulong>(rentedResults = ArrayPool<ulong>.Shared.Rent(count), 0, count);
for (int i = 0; i < count; i++)
{
workDivisors[i] = divisors[indices[i]];
}
for (int i = 0; i < count; i++)
{
workDivisors[i] = divisors[indices[i]];
}
ComputeCyclesGpuCore(workDivisors, workResults);
ComputeCyclesGpuCore(workDivisors, workResults);
for (int i = 0; i < count; i++)
{
cycles[indices[i]] = workResults[i];
}
for (int i = 0; i < count; i++)
{
cycles[indices[i]] = workResults[i];
}
if (rentedDivisors is not null)
{
ThreadStaticPools.UlongPool.Return(rentedDivisors, clearArray: false);
ThreadStaticPools.UlongPool.Return(rentedResults!, clearArray: false);
}
}
if (rentedDivisors is not null)
{
ArrayPool<ulong>.Shared.Return(rentedDivisors, clearArray: false);
ArrayPool<ulong>.Shared.Return(rentedResults!, clearArray: false);
}
}
private const int DefaultCapacity = 128;
private void ComputeCyclesGpuCore(ReadOnlySpan<ulong> divisors, Span<ulong> destination)
{
int length = divisors.Length;
var gpuLease = GpuKernelPool.GetKernel(useGpuOrder: true);
[ThreadStatic]
private static MemoryBuffer1D<ulong, Stride1D.Dense>? divisorBuffer;
Accelerator accelerator = gpuLease.Accelerator;
var kernel = _gpuKernelCache.GetOrAdd(accelerator, LoadKernel);
[ThreadStatic]
private static MemoryBuffer1D<ulong, Stride1D.Dense>? powBuffer;
using MemoryBuffer1D<ulong, Stride1D.Dense> divisorBuffer = accelerator.Allocate1D<ulong>(length);
using MemoryBuffer1D<ulong, Stride1D.Dense> powBuffer = accelerator.Allocate1D<ulong>(length);
using MemoryBuffer1D<ulong, Stride1D.Dense> orderBuffer = accelerator.Allocate1D<ulong>(length);
using MemoryBuffer1D<ulong, Stride1D.Dense> resultBuffer = accelerator.Allocate1D<ulong>(length);
using MemoryBuffer1D<byte, Stride1D.Dense> statusBuffer = accelerator.Allocate1D<byte>(length);
[ThreadStatic]
private static MemoryBuffer1D<ulong, Stride1D.Dense>? orderBuffer;
ulong[]? rentedPow = null;
Span<ulong> powSpan = length <= StackBufferThreshold
? stackalloc ulong[length]
: new Span<ulong>(rentedPow = ArrayPool<ulong>.Shared.Rent(length), 0, length);
[ThreadStatic]
private static MemoryBuffer1D<ulong, Stride1D.Dense>? resultBuffer;
ulong[]? rentedOrder = null;
Span<ulong> orderSpan = length <= StackBufferThreshold
? stackalloc ulong[length]
: new Span<ulong>(rentedOrder = ArrayPool<ulong>.Shared.Rent(length), 0, length);
[ThreadStatic]
private static MemoryBuffer1D<byte, Stride1D.Dense>? statusBuffer;
ulong[]? rentedResult = null;
Span<ulong> resultSpan = length <= StackBufferThreshold
? stackalloc ulong[length]
: new Span<ulong>(rentedResult = ArrayPool<ulong>.Shared.Rent(length), 0, length);
private void EnsureCapacity(int requiredCapacity)
{
if (requiredCapacity <= (divisorBuffer?.Length ?? 0))
{
return;
}
byte[]? rentedStatus = null;
Span<byte> statusSpan = length <= StackBufferThreshold
? stackalloc byte[length]
: new Span<byte>(rentedStatus = ArrayPool<byte>.Shared.Rent(length), 0, length);
if (divisorBuffer != null)
{
divisorBuffer.Dispose();
powBuffer!.Dispose();
orderBuffer!.Dispose();
resultBuffer!.Dispose();
statusBuffer!.Dispose();
}
ref ulong divisorRef = ref MemoryMarshal.GetReference(divisors);
divisorBuffer.View.CopyFromCPU(ref divisorRef, length);
Accelerator accelerator = _accelerator;
lock(accelerator)
{
divisorBuffer = accelerator.Allocate1D<ulong>(requiredCapacity);
powBuffer = accelerator.Allocate1D<ulong>(requiredCapacity);
orderBuffer = accelerator.Allocate1D<ulong>(requiredCapacity);
resultBuffer = accelerator.Allocate1D<ulong>(requiredCapacity);
statusBuffer = accelerator.Allocate1D<byte>(requiredCapacity);
}
}
for (int i = 0; i < length; i++)
{
ulong divisor = divisors[i];
ulong initialPow = 2UL;
if (initialPow >= divisor)
{
initialPow -= divisor;
}
private void ComputeCyclesGpuCore(ReadOnlySpan<ulong> divisors, Span<ulong> destination)
{
int length = divisors.Length;
powSpan[i] = initialPow;
orderSpan[i] = 1UL;
resultSpan[i] = 0UL;
statusSpan[i] = ByteZero;
}
EnsureCapacity(length);
powBuffer.View.CopyFromCPU(ref MemoryMarshal.GetReference(powSpan), length);
orderBuffer.View.CopyFromCPU(ref MemoryMarshal.GetReference(orderSpan), length);
resultBuffer.View.CopyFromCPU(ref MemoryMarshal.GetReference(resultSpan), length);
statusBuffer.View.CopyFromCPU(ref MemoryMarshal.GetReference(statusSpan), length);
ulong[]? rentedPow = null;
Span<ulong> powSpan = length <= StackBufferThreshold
? stackalloc ulong[length]
: new Span<ulong>(rentedPow = ThreadStaticPools.UlongPool.Rent(length), 0, length);
int pending;
do
{
kernel(length, _divisorCyclesBatchSize, divisorBuffer.View, powBuffer.View, orderBuffer.View, resultBuffer.View, statusBuffer.View);
accelerator.Synchronize();
ulong[]? rentedOrder = null;
Span<ulong> orderSpan = length <= StackBufferThreshold
? stackalloc ulong[length]
: new Span<ulong>(rentedOrder = ThreadStaticPools.UlongPool.Rent(length), 0, length);
statusBuffer.View.CopyToCPU(ref MemoryMarshal.GetReference(statusSpan), length);
pending = 0;
for (int i = 0; i < length; i++)
{
if (statusSpan[i] == ByteZero)
{
pending++;
}
}
}
while (pending > 0);
ulong[]? rentedResult = null;
Span<ulong> resultSpan = length <= StackBufferThreshold
? stackalloc ulong[length]
: new Span<ulong>(rentedResult = ThreadStaticPools.UlongPool.Rent(length), 0, length);
resultBuffer.View.CopyToCPU(ref MemoryMarshal.GetReference(resultSpan), length);
resultSpan.CopyTo(destination);
if (rentedPow is not null)
{
ArrayPool<ulong>.Shared.Return(rentedPow, clearArray: false);
ArrayPool<ulong>.Shared.Return(rentedOrder!, clearArray: false);
ArrayPool<ulong>.Shared.Return(rentedResult!, clearArray: false);
ArrayPool<byte>.Shared.Return(rentedStatus!, clearArray: false);
}
byte[]? rentedStatus = null;
Span<byte> statusSpan = length <= StackBufferThreshold
? stackalloc byte[length]
: new Span<byte>(rentedStatus = ThreadStaticPools.BytePool.Rent(length), 0, length);
gpuLease.Dispose();
}
for (int i = 0; i < length; i++)
{
ulong divisor = divisors[i];
ulong initialPow = 2UL;
if (initialPow >= divisor)
{
initialPow -= divisor;
}
private static Action<Index1D, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<byte, Stride1D.Dense>> LoadKernel(Accelerator accelerator)
{
return accelerator.LoadAutoGroupedStreamKernel<Index1D, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<byte, Stride1D.Dense>>(DivisorCycleKernels.GpuAdvanceDivisorCyclesKernel);
}
powSpan[i] = initialPow;
orderSpan[i] = 1UL;
resultSpan[i] = 0UL;
statusSpan[i] = ByteZero;
}
private sealed class AcceleratorReferenceComparer : IEqualityComparer<Accelerator>
{
internal static AcceleratorReferenceComparer Instance { get; } = new();
// GpuPrimeWorkLimiter.Acquire();
int pending;
var kernel = _gpuKernel;
var acceleratorIndex = _acceleratorIndex;
var stream = AcceleratorStreamPool.Rent(acceleratorIndex);
public bool Equals(Accelerator? x, Accelerator? y) => ReferenceEquals(x, y);
divisorBuffer!.View.CopyFromCPU(stream, divisors);
powBuffer!.View.CopyFromCPU(stream, powSpan);
orderBuffer!.View.CopyFromCPU(stream, orderSpan);
resultBuffer!.View.CopyFromCPU(stream, resultSpan);
statusBuffer!.View.CopyFromCPU(stream, statusSpan);
do
{
kernel(stream, length, _divisorCyclesBatchSize, divisorBuffer.View, powBuffer.View, orderBuffer.View, resultBuffer.View, statusBuffer.View);
statusBuffer.View.CopyToCPU(stream, statusSpan);
stream.Synchronize();
pending = 0;
for (int i = 0; i < length; i++)
{
if (statusSpan[i] == ByteZero)
{
pending++;
}
}
}
while (pending > 0);
resultBuffer.View.CopyToCPU(stream, resultSpan);
stream.Synchronize();
AcceleratorStreamPool.Return(acceleratorIndex, stream);
resultSpan.CopyTo(destination);
if (rentedPow is not null)
{
ThreadStaticPools.UlongPool.Return(rentedPow, clearArray: false);
ThreadStaticPools.UlongPool.Return(rentedOrder!, clearArray: false);
ThreadStaticPools.UlongPool.Return(rentedResult!, clearArray: false);
ThreadStaticPools.BytePool.Return(rentedStatus!, clearArray: false);
}
// GpuPrimeWorkLimiter.Release();
}
private static Action<AcceleratorStream, Index1D, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<byte, Stride1D.Dense>> LoadKernel(Accelerator accelerator)
{
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<byte, Stride1D.Dense>>(DivisorCycleKernels.GpuAdvanceDivisorCyclesKernel);
var kernel = KernelUtil.GetKernel(loaded);
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<byte, Stride1D.Dense>>>();
}
private sealed class AcceleratorReferenceComparer : IEqualityComparer<Accelerator>
{
internal static AcceleratorReferenceComparer Instance { get; } = new();
public bool Equals(Accelerator? x, Accelerator? y) => ReferenceEquals(x, y);
public int GetHashCode(Accelerator obj) => RuntimeHelpers.GetHashCode(obj);
}
public int GetHashCode(Accelerator obj) => RuntimeHelpers.GetHashCode(obj);
}
}
+2
View File
@@ -1,3 +1,5 @@
using System;
using System.Collections.Generic;
using System.Runtime.CompilerServices;
namespace PerfectNumbers.Core;
@@ -1,61 +0,0 @@
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu
{
public struct AcceleratorPool
{
internal readonly Context Context;
internal readonly Device Device;
internal readonly Accelerator[] Accelerators;
private int _index;
public int Rent()
{
Atomic.CompareExchange(ref _index, Capacity, 0);
var index = Atomic.Add(ref _index, 1);
if (index >= Capacity)
{
index -= Capacity;
}
return index;
}
public void Return(int acceleratorIndex)
{
// Intentionally left empty - there's nothing to do here. We're not really renting anything.
}
public static readonly AcceleratorPool Shared = new(PerfectNumberConstants.RollingAccelerators);
private readonly int Capacity;
public AcceleratorPool(int capacity)
{
Console.WriteLine("Creating accelerators");
Capacity = capacity;
var context = Context.CreateDefault();
var device = context.GetPreferredDevice(false);
Context = context;
Device = device;
int acceleratorsInContext = 0;
int acceleratorIndex = 0;
Accelerators = [.. Enumerable.Range(0, capacity).Select(_ =>
{
Console.WriteLine($"Preparing accelerator {acceleratorIndex++}");
Accelerator accelerator = device.CreateAccelerator(context);
acceleratorsInContext++;
if (acceleratorsInContext >= 128)
{
context = Context.CreateDefault();
device = context.GetPreferredDevice(false);
acceleratorsInContext = 0;
}
return accelerator;
})];
}
}
}
@@ -1,13 +0,0 @@
using System.Runtime.CompilerServices;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
internal sealed class AcceleratorReferenceComparer : IEqualityComparer<Accelerator>
{
internal static AcceleratorReferenceComparer Instance { get; } = new();
public bool Equals(Accelerator? x, Accelerator? y) => ReferenceEquals(x, y);
public int GetHashCode(Accelerator obj) => RuntimeHelpers.GetHashCode(obj);
}
@@ -1,34 +0,0 @@
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu.Accelerators;
public static class AcceleratorExtensions
{
public static MemoryBuffer1D<ulong, Stride1D.Dense> CopySpanToDevice(this Accelerator accelerator, AcceleratorStream stream, in ulong[] span)
{
MemoryBuffer1D<ulong, Stride1D.Dense>? buffer;
buffer = accelerator.Allocate1D(stream, span);
return buffer;
}
public static MemoryBuffer1D<ulong, Stride1D.Dense> CopyUintSpanToDevice(this Accelerator accelerator, AcceleratorStream stream, ReadOnlySpan<uint> span)
{
MemoryBuffer1D<ulong, Stride1D.Dense>? buffer;
buffer = accelerator.Allocate1D<ulong>(span.Length);
if (!span.IsEmpty)
{
var converted = new ulong[span.Length];
for (int i = 0; i < span.Length; i++)
{
converted[i] = span[i];
}
buffer.View.CopyFromCPU(stream, converted);
}
return buffer;
}
}
@@ -1,42 +0,0 @@
using System.Collections.Concurrent;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu.Accelerators;
public static class AcceleratorStreamPool
{
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
private static readonly SemaphoreSlim[] _locks = new SemaphoreSlim[PerfectNumberConstants.RollingAccelerators];
private static readonly ConcurrentQueue<AcceleratorStream>[] _streams = new ConcurrentQueue<AcceleratorStream> [PerfectNumberConstants.RollingAccelerators];
private static SemaphoreSlim CreateLock() => new(PerfectNumberConstants.ThreadsByAccelerator);
// private static int _rented;
public static AcceleratorStream Rent(int acceleratorIndex)
{
var streamLock = _locks[acceleratorIndex];
var queue = _streams[acceleratorIndex];
streamLock.Wait();
return queue.TryDequeue(out var stream)
? stream
: _accelerators[acceleratorIndex].CreateStream();
}
public static void Return(int acceleratorIndex, AcceleratorStream stream)
{
var streamLock = _locks[acceleratorIndex];
var queue = _streams[acceleratorIndex];
queue.Enqueue(stream);
streamLock.Release();
}
public static void WarmUp(int acceleratorIndex)
{
_streams[acceleratorIndex] = new();
_locks[acceleratorIndex] = CreateLock();
}
}
@@ -1,69 +0,0 @@
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu.Accelerators;
internal readonly struct HeuristicCombinedGpuTables
{
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
private static readonly HeuristicCombinedGpuTables[] _sharedTables = new HeuristicCombinedGpuTables[PerfectNumberConstants.RollingAccelerators];
internal static void WarmUp(int acceleratorIndex, AcceleratorStream stream) => _sharedTables[acceleratorIndex] = new(_accelerators[acceleratorIndex], stream);
internal static HeuristicCombinedGpuTables GetStaticTables(int acceleratorIndex) => _sharedTables[acceleratorIndex];
internal HeuristicCombinedGpuTables(Accelerator accelerator, AcceleratorStream stream)
{
var combinedEnding1 = HeuristicCombinedPrimeTester.CombinedDivisorsEnding1;
HeuristicCombinedDivisorsEnding1 = accelerator.CopySpanToDevice(stream, combinedEnding1);
var combinedSquaresEnding1 = HeuristicCombinedPrimeTester.CombinedDivisorsEnding1Squares;
HeuristicCombinedDivisorSquaresEnding1 = accelerator.CopySpanToDevice(stream, combinedSquaresEnding1);
var combinedEnding3 = HeuristicCombinedPrimeTester.CombinedDivisorsEnding3;
HeuristicCombinedDivisorsEnding3 = accelerator.CopySpanToDevice(stream, combinedEnding3);
var combinedSquaresEnding3 = HeuristicCombinedPrimeTester.CombinedDivisorsEnding3Squares;
HeuristicCombinedDivisorSquaresEnding3 = accelerator.CopySpanToDevice(stream, combinedSquaresEnding3);
var combinedEnding7 = HeuristicCombinedPrimeTester.CombinedDivisorsEnding7;
HeuristicCombinedDivisorsEnding7 = accelerator.CopySpanToDevice(stream, combinedEnding7);
var combinedSquaresEnding7 = HeuristicCombinedPrimeTester.CombinedDivisorsEnding7Squares;
HeuristicCombinedDivisorSquaresEnding7 = accelerator.CopySpanToDevice(stream, combinedSquaresEnding7);
var combinedEnding9 = HeuristicCombinedPrimeTester.CombinedDivisorsEnding9;
HeuristicCombinedDivisorsEnding9 = accelerator.CopySpanToDevice(stream, combinedEnding9);
var combinedSquaresEnding9 = HeuristicCombinedPrimeTester.CombinedDivisorsEnding9Squares;
HeuristicCombinedDivisorSquaresEnding9 = accelerator.CopySpanToDevice(stream, combinedSquaresEnding9);
}
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicCombinedDivisorsEnding1;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicCombinedDivisorSquaresEnding1;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicCombinedDivisorsEnding3;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicCombinedDivisorSquaresEnding3;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicCombinedDivisorsEnding7;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicCombinedDivisorSquaresEnding7;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicCombinedDivisorsEnding9;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicCombinedDivisorSquaresEnding9;
internal HeuristicCombinedGpuViews CreateViews() => new(
HeuristicCombinedDivisorsEnding1.View,
HeuristicCombinedDivisorsEnding3.View,
HeuristicCombinedDivisorsEnding7.View,
HeuristicCombinedDivisorsEnding9.View,
HeuristicCombinedDivisorSquaresEnding1.View,
HeuristicCombinedDivisorSquaresEnding3.View,
HeuristicCombinedDivisorSquaresEnding7.View,
HeuristicCombinedDivisorSquaresEnding9.View);
internal void Dispose()
{
HeuristicCombinedDivisorsEnding1.Dispose();
HeuristicCombinedDivisorSquaresEnding1.Dispose();
HeuristicCombinedDivisorsEnding3.Dispose();
HeuristicCombinedDivisorSquaresEnding3.Dispose();
HeuristicCombinedDivisorsEnding7.Dispose();
HeuristicCombinedDivisorSquaresEnding7.Dispose();
HeuristicCombinedDivisorsEnding9.Dispose();
HeuristicCombinedDivisorSquaresEnding9.Dispose();
}
}
@@ -1,45 +0,0 @@
using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu.Accelerators;
public readonly struct HeuristicCombinedGpuViews(
ArrayView1D<ulong, Stride1D.Dense> combinedDivisorsEnding1,
ArrayView1D<ulong, Stride1D.Dense> combinedDivisorsEnding3,
ArrayView1D<ulong, Stride1D.Dense> combinedDivisorsEnding7,
ArrayView1D<ulong, Stride1D.Dense> combinedDivisorsEnding9,
ArrayView1D<ulong, Stride1D.Dense> combinedDivisorSquaresEnding1,
ArrayView1D<ulong, Stride1D.Dense> combinedDivisorSquaresEnding3,
ArrayView1D<ulong, Stride1D.Dense> combinedDivisorSquaresEnding7,
ArrayView1D<ulong, Stride1D.Dense> combinedDivisorSquaresEnding9)
{
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorsEnding1 = combinedDivisorsEnding1;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorsEnding3 = combinedDivisorsEnding3;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorsEnding7 = combinedDivisorsEnding7;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorsEnding9 = combinedDivisorsEnding9;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorSquaresEnding1 = combinedDivisorSquaresEnding1;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorSquaresEnding3 = combinedDivisorSquaresEnding3;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorSquaresEnding7 = combinedDivisorSquaresEnding7;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorSquaresEnding9 = combinedDivisorSquaresEnding9;
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ArrayView1D<ulong, Stride1D.Dense> SelectDivisors(byte ending) => ending switch
{
1 => CombinedDivisorsEnding1,
3 => CombinedDivisorsEnding3,
7 => CombinedDivisorsEnding7,
9 => CombinedDivisorsEnding9,
_ => ArrayView1D<ulong, Stride1D.Dense>.Empty,
};
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ArrayView1D<ulong, Stride1D.Dense> SelectDivisorSquares(byte ending) => ending switch
{
1 => CombinedDivisorSquaresEnding1,
3 => CombinedDivisorSquaresEnding3,
7 => CombinedDivisorSquaresEnding7,
9 => CombinedDivisorSquaresEnding9,
_ => ArrayView1D<ulong, Stride1D.Dense>.Empty,
};
}
@@ -1,79 +0,0 @@
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu.Accelerators;
internal sealed class HeuristicGroupABGpuTables
{
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
private static readonly HeuristicGroupABGpuTables[] _sharedTables = new HeuristicGroupABGpuTables[PerfectNumberConstants.RollingAccelerators];
private static readonly SemaphoreSlim[] _locks = [..Enumerable.Range(1, PerfectNumberConstants.RollingAccelerators).Select(_ => new SemaphoreSlim(1))];
internal static HeuristicGroupABGpuTables EnsureStaticTables(int acceleratorIndex, AcceleratorStream stream)
{
var @lock = _locks[acceleratorIndex];
@lock.Wait();
if (_sharedTables[acceleratorIndex] is {} existing)
{
@lock.Release();
return existing;
}
var accelerator = _accelerators[acceleratorIndex];
existing = new(accelerator, stream);
_sharedTables[acceleratorIndex] = existing;
@lock.Release();
return existing;
}
internal HeuristicGroupABGpuTables(Accelerator accelerator, AcceleratorStream stream)
{
var heuristicGroupA = HeuristicPrimeSieves.GroupADivisorsStorage;
HeuristicGroupADivisors = accelerator.CopySpanToDevice(stream, heuristicGroupA);
var heuristicGroupASquares = HeuristicPrimeSieves.GroupADivisorSquaresStorage;
HeuristicGroupADivisorSquares = accelerator.CopySpanToDevice(stream, heuristicGroupASquares);
HeuristicGroupBDivisorsEnding1 = accelerator.CopyUintSpanToDevice(stream, DivisorGenerator.SmallPrimesLastOneWithoutLastThree);
HeuristicGroupBDivisorSquaresEnding1 = accelerator.CopySpanToDevice(stream, DivisorGenerator.SmallPrimesPow2LastOneWithoutLastThree);
HeuristicGroupBDivisorsEnding7 = accelerator.CopyUintSpanToDevice(stream, DivisorGenerator.SmallPrimesLastSevenWithoutLastThree);
HeuristicGroupBDivisorSquaresEnding7 = accelerator.CopySpanToDevice(stream, DivisorGenerator.SmallPrimesPow2LastSevenWithoutLastThree);
HeuristicGroupBDivisorsEnding9 = accelerator.CopyUintSpanToDevice(stream, DivisorGenerator.SmallPrimesLastNineWithoutLastThree);
HeuristicGroupBDivisorSquaresEnding9 = accelerator.CopySpanToDevice(stream, DivisorGenerator.SmallPrimesPow2LastNineWithoutLastThree);
}
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupADivisors;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupADivisorSquares;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupBDivisorsEnding1;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupBDivisorSquaresEnding1;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupBDivisorsEnding7;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupBDivisorSquaresEnding7;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupBDivisorsEnding9;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupBDivisorSquaresEnding9;
internal HeuristicGroupABGpuViews CreateViews() => new(
HeuristicGroupADivisors.View,
HeuristicGroupADivisorSquares.View,
HeuristicGroupBDivisorsEnding1.View,
HeuristicGroupBDivisorSquaresEnding1.View,
HeuristicGroupBDivisorsEnding7.View,
HeuristicGroupBDivisorSquaresEnding7.View,
HeuristicGroupBDivisorsEnding9.View,
HeuristicGroupBDivisorSquaresEnding9.View);
internal void Dispose()
{
HeuristicGroupADivisors.Dispose();
HeuristicGroupADivisorSquares.Dispose();
HeuristicGroupBDivisorsEnding1.Dispose();
HeuristicGroupBDivisorSquaresEnding1.Dispose();
HeuristicGroupBDivisorsEnding7.Dispose();
HeuristicGroupBDivisorSquaresEnding7.Dispose();
HeuristicGroupBDivisorsEnding9.Dispose();
HeuristicGroupBDivisorSquaresEnding9.Dispose();
}
}
@@ -1,63 +0,0 @@
using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu.Accelerators;
public readonly struct HeuristicGroupABGpuViews(
ArrayView1D<ulong, Stride1D.Dense> groupADivisors,
ArrayView1D<ulong, Stride1D.Dense> groupADivisorSquares,
ArrayView1D<ulong, Stride1D.Dense> groupBDivisorsEnding1,
ArrayView1D<ulong, Stride1D.Dense> groupBDivisorSquaresEnding1,
ArrayView1D<ulong, Stride1D.Dense> groupBDivisorsEnding7,
ArrayView1D<ulong, Stride1D.Dense> groupBDivisorSquaresEnding7,
ArrayView1D<ulong, Stride1D.Dense> groupBDivisorsEnding9,
ArrayView1D<ulong, Stride1D.Dense> groupBDivisorSquaresEnding9)
{
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupADivisors = groupADivisors;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupADivisorSquares = groupADivisorSquares;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorsEnding1 = groupBDivisorsEnding1;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorSquaresEnding1 = groupBDivisorSquaresEnding1;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorsEnding7 = groupBDivisorsEnding7;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorSquaresEnding7 = groupBDivisorSquaresEnding7;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorsEnding9 = groupBDivisorsEnding9;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorSquaresEnding9 = groupBDivisorSquaresEnding9;
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ArrayView1D<ulong, Stride1D.Dense> SelectGroupB(byte ending) => ending switch
{
1 => GroupBDivisorsEnding1,
7 => GroupBDivisorsEnding7,
9 => GroupBDivisorsEnding9,
_ => ArrayView1D<ulong, Stride1D.Dense>.Empty,
};
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ArrayView1D<ulong, Stride1D.Dense> SelectGroupBSquares(byte ending) => ending switch
{
1 => GroupBDivisorSquaresEnding1,
7 => GroupBDivisorSquaresEnding7,
9 => GroupBDivisorSquaresEnding9,
_ => ArrayView1D<ulong, Stride1D.Dense>.Empty,
};
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ArrayView1D<ulong, Stride1D.Dense> SelectDivisors(HeuristicGpuDivisorTableKind kind) => kind switch
{
HeuristicGpuDivisorTableKind.GroupA => GroupADivisors,
HeuristicGpuDivisorTableKind.GroupBEnding1 => GroupBDivisorsEnding1,
HeuristicGpuDivisorTableKind.GroupBEnding7 => GroupBDivisorsEnding7,
HeuristicGpuDivisorTableKind.GroupBEnding9 => GroupBDivisorsEnding9,
_ => ArrayView1D<ulong, Stride1D.Dense>.Empty,
};
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ArrayView1D<ulong, Stride1D.Dense> SelectDivisorSquares(HeuristicGpuDivisorTableKind kind) => kind switch
{
HeuristicGpuDivisorTableKind.GroupA => GroupADivisorSquares,
HeuristicGpuDivisorTableKind.GroupBEnding1 => GroupBDivisorSquaresEnding1,
HeuristicGpuDivisorTableKind.GroupBEnding7 => GroupBDivisorSquaresEnding7,
HeuristicGpuDivisorTableKind.GroupBEnding9 => GroupBDivisorSquaresEnding9,
_ => ArrayView1D<ulong, Stride1D.Dense>.Empty,
};
}
@@ -1,174 +0,0 @@
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu.Accelerators;
internal sealed class HeuristicGroupABPrimeTesterAccelerator
{
#region Pool
[ThreadStatic]
private static Queue<HeuristicGroupABPrimeTesterAccelerator>? Pool;
internal static void WarmUp()
{
Accelerator[]? accelerators = AcceleratorPool.Shared.Accelerators;
int acceleratorCount = accelerators.Length;
for (var i = 0; i < acceleratorCount; i++)
{
Console.WriteLine($"Preparing heuristic accelerator {i}...");
var accelerator = accelerators[i];
AcceleratorStream stream = accelerator.CreateStream();
_ = HeuristicGroupABGpuTables.EnsureStaticTables(i, stream);
// _ = GpuKernelPool.GetOrAddKernels(accelerator, stream, KernelType.None);
// KernelContainer kernels = GpuKernelPool.GetOrAddKernels(accelerator, stream);
// GpuStaticTableInitializer.EnsureStaticTables(accelerator, kernels, stream);
stream.Synchronize();
stream.Dispose();
Console.WriteLine($"Heuristic accelerator {i} is ready");
}
}
internal static HeuristicGroupABPrimeTesterAccelerator Rent(int minBufferCapacity = 1)
{
var pool = Pool ??= new();
if (!pool.TryDequeue(out var lease))
{
lease = new HeuristicGroupABPrimeTesterAccelerator(minBufferCapacity);
}
else
{
lease.EnsureCapacity(minBufferCapacity);
}
return lease;
}
internal static void Return(HeuristicGroupABPrimeTesterAccelerator lease)
{
var pool = Pool ??= new();
pool.Enqueue(lease);
}
internal static void DisposeAll()
{
if (Pool != null)
{
while (Pool.TryDequeue(out var lease))
{
lease.DisposeResources();
}
}
}
internal static void Clear()
{
if (Pool != null)
{
var retained = new List<HeuristicGroupABPrimeTesterAccelerator>();
while (Pool.TryDequeue(out var lease))
{
lease.DisposeResources();
}
}
}
#endregion
public readonly HeuristicGroupABGpuViews DivisorTables;
internal readonly Context Context;
public readonly Accelerator Accelerator;
[ThreadStatic]
public static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<ulong>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<byte>>>? SmallPrimeSieveKernel;
internal static Action<AcceleratorStream, Index1D, ArrayView<ulong>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<byte>> GetSmallPrimeSieveKernel(Accelerator accelerator)
{
var pool = SmallPrimeSieveKernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
cached = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<ulong>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<byte>>(PrimeTesterKernels.SmallPrimeSieveKernel)).CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<ulong>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<byte>>>();
pool[accelerator] = cached;
return cached;
}
public readonly Kernel HeuristicTrialDivisionKernel;
public MemoryBuffer1D<ulong, Stride1D.Dense>? Input = null;
public MemoryBuffer1D<byte, Stride1D.Dense>? Output = null;
public MemoryBuffer1D<int, Stride1D.Dense>? HeuristicFlag = null!;
public int BufferCapacity;
private HeuristicGroupABGpuTables _sharedTables;
public MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupADivisors => _sharedTables.HeuristicGroupADivisors;
public MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupADivisorSquares => _sharedTables.HeuristicGroupADivisorSquares;
public MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupBDivisorsEnding1 => _sharedTables.HeuristicGroupBDivisorsEnding1;
public MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupBDivisorSquaresEnding1 => _sharedTables.HeuristicGroupBDivisorSquaresEnding1;
public MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupBDivisorsEnding7 => _sharedTables.HeuristicGroupBDivisorsEnding7;
public MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupBDivisorSquaresEnding7 => _sharedTables.HeuristicGroupBDivisorSquaresEnding7;
public MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupBDivisorsEnding9 => _sharedTables.HeuristicGroupBDivisorsEnding9;
public MemoryBuffer1D<ulong, Stride1D.Dense> HeuristicGroupBDivisorSquaresEnding9 => _sharedTables.HeuristicGroupBDivisorSquaresEnding9;
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
internal readonly int AcceleratorIndex;
internal HeuristicGroupABPrimeTesterAccelerator(int minBufferCapacity)
{
var acceleratorIndex = AcceleratorPool.Shared.Rent();
AcceleratorIndex = acceleratorIndex;
Accelerator accelerator = _accelerators[acceleratorIndex];
Context = accelerator.Context;
Accelerator = accelerator;
EnsureCapacity(minBufferCapacity);
HeuristicTrialDivisionKernel = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<int>, ulong, ulong, HeuristicGpuDivisorTableKind, HeuristicGroupABGpuViews>(PrimeTesterKernels.HeuristicTrialGroupABDivisionKernel));
AcceleratorStream stream = AcceleratorStreamPool.Rent(acceleratorIndex);
// GpuStaticTableInitializer.EnsureStaticTables(accelerator, kernels, stream);
_sharedTables = HeuristicGroupABGpuTables.EnsureStaticTables(acceleratorIndex, stream);
DivisorTables = _sharedTables.CreateViews();
stream.Synchronize();
AcceleratorStreamPool.Return(acceleratorIndex, stream);
}
public void EnsureCapacity(int minCapacity)
{
if (minCapacity <= BufferCapacity)
{
return;
}
Input?.Dispose();
Output?.Dispose();
HeuristicFlag?.Dispose();
Input = Accelerator.Allocate1D<ulong>(minCapacity);
Output = Accelerator.Allocate1D<byte>(minCapacity);
HeuristicFlag = Accelerator.Allocate1D<int>(minCapacity);
BufferCapacity = minCapacity;
}
public void Dispose()
{
Return(this);
}
internal void DisposeResources()
{
Input?.Dispose();
Output?.Dispose();
HeuristicFlag?.Dispose();
// ReleaseSharedTables(_sharedTables);
// These resources are shared between GPU leases
// Accelerator.Dispose();
// AcceleratorContext.Dispose();
}
}
@@ -1,58 +0,0 @@
using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu.Accelerators;
internal readonly struct LastDigitGpuTables
{
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
private static readonly LastDigitGpuTables[] _sharedTables = new LastDigitGpuTables[PerfectNumberConstants.RollingAccelerators];
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static LastDigitGpuTables GetStaticTables(int acceleratorIndex) => _sharedTables[acceleratorIndex];
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static void WarmUp(int acceleratorIndex, AcceleratorStream stream) => _sharedTables[acceleratorIndex] = new LastDigitGpuTables(_accelerators[acceleratorIndex], stream);
internal LastDigitGpuTables(Accelerator accelerator, AcceleratorStream stream)
{
var primesLastOne = DivisorGenerator.SmallPrimesLastOne;
var primesLastSeven = DivisorGenerator.SmallPrimesLastSeven;
var primesLastThree = DivisorGenerator.SmallPrimesLastThree;
var primesLastNine = DivisorGenerator.SmallPrimesLastNine;
var primesPow2LastOne = DivisorGenerator.SmallPrimesPow2LastOne;
var primesPow2LastSeven = DivisorGenerator.SmallPrimesPow2LastSeven;
var primesPow2LastThree = DivisorGenerator.SmallPrimesPow2LastThree;
var primesPow2LastNine = DivisorGenerator.SmallPrimesPow2LastNine;
DevicePrimesLastOne = accelerator.Allocate1D(stream, primesLastOne);
DevicePrimesLastSeven = accelerator.Allocate1D(stream, primesLastSeven);
DevicePrimesLastThree = accelerator.Allocate1D(stream, primesLastThree);
DevicePrimesLastNine = accelerator.Allocate1D(stream, primesLastNine);
DevicePrimesPow2LastOne = accelerator.Allocate1D(stream, primesPow2LastOne);
DevicePrimesPow2LastSeven = accelerator.Allocate1D(stream, primesPow2LastSeven);
DevicePrimesPow2LastThree = accelerator.Allocate1D(stream, primesPow2LastThree);
DevicePrimesPow2LastNine = accelerator.Allocate1D(stream, primesPow2LastNine);
}
internal readonly MemoryBuffer1D<uint, Stride1D.Dense> DevicePrimesLastOne;
internal readonly MemoryBuffer1D<uint, Stride1D.Dense> DevicePrimesLastSeven;
internal readonly MemoryBuffer1D<uint, Stride1D.Dense> DevicePrimesLastThree;
internal readonly MemoryBuffer1D<uint, Stride1D.Dense> DevicePrimesLastNine;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> DevicePrimesPow2LastOne;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> DevicePrimesPow2LastSeven;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> DevicePrimesPow2LastThree;
internal readonly MemoryBuffer1D<ulong, Stride1D.Dense> DevicePrimesPow2LastNine;
internal void Dispose()
{
DevicePrimesLastOne.Dispose();
DevicePrimesLastSeven.Dispose();
DevicePrimesLastThree.Dispose();
DevicePrimesLastNine.Dispose();
DevicePrimesPow2LastOne.Dispose();
DevicePrimesPow2LastSeven.Dispose();
DevicePrimesPow2LastThree.Dispose();
DevicePrimesPow2LastNine.Dispose();
}
}
@@ -1,300 +0,0 @@
using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Runtime;
using PerfectNumbers.Core.Gpu.Kernels;
namespace PerfectNumbers.Core.Gpu.Accelerators;
public sealed class PrimeOrderCalculatorAccelerator
{
#region Pool
[ThreadStatic]
private static Queue<PrimeOrderCalculatorAccelerator>? _pool;
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static PrimeOrderCalculatorAccelerator Rent(int primeTesterCapacity)
{
var pool = _pool ??= [];
if (!pool.TryDequeue(out var gpu))
{
int acceleratorIndex = AcceleratorPool.Shared.Rent();
gpu = new(acceleratorIndex, PerfectNumberConstants.DefaultFactorsBuffer, primeTesterCapacity, PerfectNumberConstants.DefaultSmallPrimeFactorSlotCount, PerfectNumberConstants.DefaultSpecialMaxFactorCapacity);
}
else
{
gpu.EnsureCapacity(PerfectNumberConstants.DefaultFactorsBuffer, primeTesterCapacity);
}
return gpu;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static void Return(PrimeOrderCalculatorAccelerator gpu) => _pool!.Enqueue(gpu);
internal static void Clear()
{
Queue<PrimeOrderCalculatorAccelerator>? pool = _pool;
if (pool != null)
{
while (pool.TryDequeue(out var gpu))
{
gpu.Dispose();
}
}
}
internal static void DisposeAll()
{
Queue<PrimeOrderCalculatorAccelerator>? pool = _pool;
if (pool != null)
{
while (pool.TryDequeue(out var gpu))
{
gpu.Dispose();
}
}
}
internal static void WarmUp()
{
Accelerator[] accelerators = AcceleratorPool.Shared.Accelerators;
int acceleratorCount = accelerators.Length;
for (var i = 0; i < acceleratorCount; i++)
{
Console.WriteLine($"Preparing accelerator {i}...");
var accelerator = accelerators[i];
AcceleratorStreamPool.WarmUp(i);
// Don't take this from the pool as quick uploads of data to the accelerator consumes much of GPU's memory and throws.
AcceleratorStream stream = accelerator.CreateStream();
// TODO: Review which tables are needed when final execution path is defined.
LastDigitGpuTables.WarmUp(i, stream);
HeuristicCombinedGpuTables.WarmUp(i, stream);
// SmallPrimeFactorGpuTables.WarmUp(i, stream);
// SharedHeuristicGpuTables.EnsureStaticTables(accelerator, stream);
// _ = GpuKernelPool.GetOrAddKernels(accelerator, stream, KernelType.None);
// KernelContainer kernels = GpuKernelPool.GetOrAddKernels(accelerator, stream);
// GpuStaticTableInitializer.EnsureStaticTables(accelerator, kernels, stream);
stream.Synchronize();
stream.Dispose();
accelerator.Synchronize();
}
}
#endregion
#region Static Tables
public readonly ArrayView1D<uint, Stride1D.Dense> DevicePrimesLastOne;
public readonly ArrayView1D<uint, Stride1D.Dense> DevicePrimesLastSeven;
public readonly ArrayView1D<uint, Stride1D.Dense> DevicePrimesLastThree;
public readonly ArrayView1D<uint, Stride1D.Dense> DevicePrimesLastNine;
public readonly ArrayView1D<ulong, Stride1D.Dense> DevicePrimesPow2LastOne;
public readonly ArrayView1D<ulong, Stride1D.Dense> DevicePrimesPow2LastSeven;
public readonly ArrayView1D<ulong, Stride1D.Dense> DevicePrimesPow2LastThree;
public readonly ArrayView1D<ulong, Stride1D.Dense> DevicePrimesPow2LastNine;
public readonly HeuristicCombinedGpuViews DivisorTables;
public readonly ArrayView1D<uint, Stride1D.Dense> SmallPrimeFactorPrimes;
public readonly ArrayView1D<ulong, Stride1D.Dense> SmallPrimeFactorSquares;
#endregion
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
public readonly Accelerator Accelerator;
public readonly int AcceleratorIndex;
public MemoryBuffer1D<ulong, Stride1D.Dense> Input;
public MemoryBuffer1D<ulong, Stride1D.Dense> OutputUlong;
public MemoryBuffer1D<byte, Stride1D.Dense> OutputByte;
public MemoryBuffer1D<int, Stride1D.Dense> OutputInt;
public MemoryBuffer1D<KeyValuePair<ulong, int>, Stride1D.Dense> Pow2ModEntriesToTestOnDevice;
public readonly MemoryBuffer1D<int, Stride1D.Dense> SmallPrimeFactorCountSlot;
public readonly MemoryBuffer1D<ulong, Stride1D.Dense> SpecialMaxResult;
public Dictionary<ulong, int> Pow2ModEntriesToTestOnHost = [];
public readonly Action<AcceleratorStream, int, ulong, ArrayView1D<KeyValuePair<ulong, int>, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>> CheckFactorsKernelLauncher;
public readonly Action<AcceleratorStream, Index1D, ArrayView1D<ulong, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>> ConvertToStandardKernelLauncher;
public readonly Action<AcceleratorStream, Index1D, byte, ArrayView<int>, ulong, ulong, HeuristicCombinedGpuViews> HeuristicCombinedTrialDivisionKernelLauncher;
public readonly Action<AcceleratorStream, Index1D, ArrayView1D<ulong, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>> KeepMontgomeryKernelLauncher;
public readonly Action<AcceleratorStream, ulong, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<byte, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>> PollardRhoKernelLauncher;
public readonly Action<AcceleratorStream, Index1D, ArrayView1D<GpuUInt128, Stride1D.Dense>, GpuUInt128, ArrayView1D<GpuUInt128, Stride1D.Dense>> Pow2ModWideKernelLauncher;
public readonly Action<AcceleratorStream, Index1D, ArrayView<ulong>, ArrayView<byte>> SharesFactorKernelLauncher;
public readonly Action<AcceleratorStream, Index1D, ulong, uint, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<int, Stride1D.Dense>, ArrayView1D<int, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>> SmallPrimeFactorKernelLauncher;
public readonly Action<AcceleratorStream, Index1D, ArrayView<ulong>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<byte>> SmallPrimeSieveKernelLauncher;
public readonly Action<AcceleratorStream, Index1D, ulong, ArrayView1D<ulong, Stride1D.Dense>, int, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>> SpecialMaxKernelLauncher;
public void EnsureCapacity(int factorsCount, int primeTesterCapacity)
{
Accelerator accelerator = Accelerator;
MemoryBuffer1D<KeyValuePair<ulong, int>, Stride1D.Dense> pow2ModEntriesToTestOnDevice = Pow2ModEntriesToTestOnDevice;
if (pow2ModEntriesToTestOnDevice.Length < factorsCount)
{
lock (accelerator)
{
pow2ModEntriesToTestOnDevice.Dispose();
Pow2ModEntriesToTestOnDevice = accelerator.Allocate1D<KeyValuePair<ulong, int>>(factorsCount);
}
}
MemoryBuffer1D<ulong, Stride1D.Dense> input = Input;
if (input.Length < primeTesterCapacity)
{
lock (accelerator)
{
input.Dispose();
Input = accelerator.Allocate1D<ulong>(primeTesterCapacity);
}
}
MemoryBuffer1D<byte, Stride1D.Dense> outputByte = OutputByte;
if (outputByte.Length < primeTesterCapacity)
{
lock (accelerator)
{
outputByte.Dispose();
OutputByte = accelerator.Allocate1D<byte>(primeTesterCapacity);
}
}
MemoryBuffer1D<int, Stride1D.Dense> outputInt = OutputInt;
if (outputInt.Length < primeTesterCapacity)
{
lock (accelerator)
{
outputInt.Dispose();
OutputInt = accelerator.Allocate1D<int>(primeTesterCapacity);
}
}
}
public void EnsureSmallPrimeFactorSlotsCapacity(int newSize)
{
// Console.WriteLine($"Resizing GPU scratch buffer from pool ({buffer.SmallPrimeFactorPrimeSlots.Length} / {smallPrimeFactorSlotCount}), ({buffer.SpecialMaxFactors.Length}/{specialMaxFactorCapacity})");
var accelerator = Accelerator;
MemoryBuffer1D<ulong, Stride1D.Dense> outputUlong = OutputUlong;
if (outputUlong.Length < newSize)
{
lock (accelerator)
{
outputUlong.Dispose();
OutputUlong = accelerator.Allocate1D<ulong>(newSize);
}
}
MemoryBuffer1D<int, Stride1D.Dense> outputInt = OutputInt;
if (outputInt.Length < newSize)
{
lock (accelerator)
{
outputInt.Dispose();
OutputInt = accelerator.Allocate1D<int>(newSize);
}
}
}
public void EnsureSpecialMaxFactorsCapacity(int newSize)
{
var accelerator = Accelerator;
MemoryBuffer1D<ulong, Stride1D.Dense> input = Input;
if (input.Length < newSize)
{
lock (accelerator)
{
input.Dispose();
Input = accelerator.Allocate1D<ulong>(newSize);
}
}
MemoryBuffer1D<ulong, Stride1D.Dense> outputUlong = OutputUlong;
if (outputUlong.Length < newSize)
{
lock (accelerator)
{
outputUlong.Dispose();
OutputUlong = accelerator.Allocate1D<ulong>(newSize);
}
}
}
public PrimeOrderCalculatorAccelerator(int acceleratorIndex, int factorsCount, int primeTesterCapacity, int smallPrimeFactorSlotCount, int specialMaxFactorCapacity)
{
var accelerator = _accelerators[acceleratorIndex];
Accelerator = accelerator;
AcceleratorIndex = acceleratorIndex;
lock (accelerator)
{
Input = accelerator.Allocate1D<ulong>(Math.Max(specialMaxFactorCapacity, primeTesterCapacity));
OutputByte = Accelerator.Allocate1D<byte>(primeTesterCapacity);
OutputInt = Accelerator.Allocate1D<int>(Math.Max(primeTesterCapacity, smallPrimeFactorSlotCount));
OutputUlong = accelerator.Allocate1D<ulong>(Math.Max(specialMaxFactorCapacity, smallPrimeFactorSlotCount));
Pow2ModEntriesToTestOnDevice = accelerator.Allocate1D<KeyValuePair<ulong, int>>(factorsCount);
SmallPrimeFactorCountSlot = accelerator.Allocate1D<int>(1);
SpecialMaxResult = accelerator.Allocate1D<ulong>(1);
LastDigitGpuTables lastDigitSharedTables = LastDigitGpuTables.GetStaticTables(acceleratorIndex);
DevicePrimesLastOne = lastDigitSharedTables.DevicePrimesLastOne.View;
DevicePrimesLastSeven = lastDigitSharedTables.DevicePrimesLastSeven.View;
DevicePrimesLastThree = lastDigitSharedTables.DevicePrimesLastThree.View;
DevicePrimesLastNine = lastDigitSharedTables.DevicePrimesLastNine.View;
DevicePrimesPow2LastOne = lastDigitSharedTables.DevicePrimesPow2LastOne.View;
DevicePrimesPow2LastSeven = lastDigitSharedTables.DevicePrimesPow2LastSeven.View;
DevicePrimesPow2LastThree = lastDigitSharedTables.DevicePrimesPow2LastThree.View;
DevicePrimesPow2LastNine = lastDigitSharedTables.DevicePrimesPow2LastNine.View;
DivisorTables = HeuristicCombinedGpuTables
.GetStaticTables(acceleratorIndex)
.CreateViews();
var smallPrimeFactorTables = SmallPrimeFactorGpuTables.GetStaticTables(acceleratorIndex);
if (smallPrimeFactorTables.HasValue)
{
SmallPrimeFactorGpuTables tables = smallPrimeFactorTables.Value;
SmallPrimeFactorPrimes = tables.Primes.View;
SmallPrimeFactorSquares = tables.Squares.View;
}
CheckFactorsKernelLauncher = KernelUtil.GetKernel(accelerator.LoadStreamKernel<int, ulong, ArrayView1D<KeyValuePair<ulong, int>, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>>(PrimeOrderGpuHeuristics.CheckFactorsKernel)).CreateLauncherDelegate<Action<AcceleratorStream, int, ulong, ArrayView1D<KeyValuePair<ulong, int>, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>>>();
ConvertToStandardKernelLauncher = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView1D<ulong, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>>(Pow2MontgomeryKernels.Pow2MontgomeryKernelConvertToStandard)).CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView1D<ulong, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>>>();
HeuristicCombinedTrialDivisionKernelLauncher = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, byte, ArrayView<int>, ulong, ulong, HeuristicCombinedGpuViews>(PrimeTesterKernels.HeuristicTrialCombinedDivisionKernel)).CreateLauncherDelegate<Action<AcceleratorStream, Index1D, byte, ArrayView<int>, ulong, ulong, HeuristicCombinedGpuViews>>();
KeepMontgomeryKernelLauncher = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView1D<ulong, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>>(Pow2MontgomeryKernels.Pow2MontgomeryKernelKeepMontgomery)).CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView1D<ulong, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>>>();
PollardRhoKernelLauncher = KernelUtil.GetKernel(accelerator.LoadStreamKernel<ulong, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<byte, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>(Pow2MontgomeryKernels.TryPollardRhoKernel)).CreateLauncherDelegate<Action<AcceleratorStream, ulong, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<byte, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>>();
Pow2ModWideKernelLauncher = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView1D<GpuUInt128, Stride1D.Dense>, GpuUInt128, ArrayView1D<GpuUInt128, Stride1D.Dense>>(PrimeOrderGpuHeuristics.Pow2ModKernelWide)).CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView1D<GpuUInt128, Stride1D.Dense>, GpuUInt128, ArrayView1D<GpuUInt128, Stride1D.Dense>>>();
SharesFactorKernelLauncher = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<ulong>, ArrayView<byte>>(PrimeTesterKernels.SharesFactorKernel)).CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<ulong>, ArrayView<byte>>>();
SmallPrimeFactorKernelLauncher = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, ulong, uint, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<int, Stride1D.Dense>, ArrayView1D<int, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>(SmallPrimeFactorKernels.SmallPrimeFactorKernelScan)).CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, uint, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<int, Stride1D.Dense>, ArrayView1D<int, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>>();
SmallPrimeSieveKernelLauncher = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<ulong>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<byte>>(PrimeTesterKernels.SmallPrimeSieveKernel)).CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<ulong>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<uint>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<ulong>, ArrayView<byte>>>();
SpecialMaxKernelLauncher = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, ulong, ArrayView1D<ulong, Stride1D.Dense>, int, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>(PrimeOrderGpuHeuristics.EvaluateSpecialMaxCandidatesKernel)).CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, ArrayView1D<ulong, Stride1D.Dense>, int, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>>();
}
}
public void Dispose()
{
Input.Dispose();
OutputByte.Dispose();
OutputInt.Dispose();
OutputUlong.Dispose();
Pow2ModEntriesToTestOnDevice.Dispose();
SmallPrimeFactorCountSlot.Dispose();
SpecialMaxResult.Dispose();
// These resources are shared between GPU leases
// Stream.Dispose();
// Accelerator.Dispose();
// Context.Dispose();
}
}
@@ -1,75 +0,0 @@
using System.Runtime.CompilerServices;
using ILGPU;
namespace PerfectNumbers.Core.Gpu;
public static class ThreadStaticDeterministicRandomGpu
{
[ThreadStatic]
private static DeterministicRandomGpu? _exclusive;
internal static DeterministicRandomGpu Exclusive => _exclusive ?? new DeterministicRandomGpu();
}
internal struct DeterministicRandomGpu
{
private static long s_seedCounter;
private ulong _state;
public readonly ulong State
{
[MethodImpl(MethodImplOptions.AggressiveInlining)]
get
{
return _state;
}
}
public DeterministicRandomGpu()
{
_state = CreateThreadState();
}
public DeterministicRandomGpu(ulong initialState)
{
_state = initialState;
}
public ulong NextUInt64()
{
ulong state = _state;
state ^= state >> 12;
state ^= state << 25;
state ^= state >> 27;
_state = state;
return state * 2685821657736338717UL;
}
public GpuUInt128 NextUInt128()
{
GpuUInt128 high = (GpuUInt128)NextUInt64();
ReadOnlyGpuUInt128 low = (ReadOnlyGpuUInt128)NextUInt64();
high.ShiftLeft(64);
high.Add(low);
return high;
}
public void SetState(ulong state)
{
_state = state;
}
private static ulong CreateThreadState()
{
ulong seed = (ulong)Atomic.Add(ref s_seedCounter, 1);
seed += 0x9E3779B97F4A7C15UL;
seed = (seed ^ (seed >> 30)) * 0xBF58476D1CE4E5B9UL;
seed = (seed ^ (seed >> 27)) * 0x94D049BB133111EBUL;
seed ^= seed >> 31;
if (seed == 0UL)
{
seed = 0x9E3779B97F4A7C15UL;
}
return seed;
}
}
@@ -0,0 +1,142 @@
using System;
using System.Collections.Concurrent;
using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
internal static class DivisorGeneratorGpuCache
{
private sealed class AcceleratorReferenceComparer : IEqualityComparer<Accelerator>
{
public static AcceleratorReferenceComparer Instance { get; } = new();
public bool Equals(Accelerator? x, Accelerator? y)
{
return ReferenceEquals(x, y);
}
public int GetHashCode(Accelerator obj)
{
return RuntimeHelpers.GetHashCode(obj);
}
}
private sealed class DivisorGeneratorGpuTables : IDisposable
{
internal DivisorGeneratorGpuTables(Accelerator accelerator)
{
SmallPrimes = AllocateAndCopyUInt(accelerator, DivisorGenerator.SmallPrimes);
SmallPrimesPow2 = AllocateAndCopyULong(accelerator, DivisorGenerator.SmallPrimesPow2);
SmallPrimesLastOne = AllocateAndCopyUInt(accelerator, DivisorGenerator.SmallPrimesLastOne);
SmallPrimesPow2LastOne = AllocateAndCopyULong(accelerator, DivisorGenerator.SmallPrimesPow2LastOne);
SmallPrimesLastSeven = AllocateAndCopyUInt(accelerator, DivisorGenerator.SmallPrimesLastSeven);
SmallPrimesPow2LastSeven = AllocateAndCopyULong(accelerator, DivisorGenerator.SmallPrimesPow2LastSeven);
SmallPrimesLastThree = AllocateAndCopyUInt(accelerator, DivisorGenerator.SmallPrimesLastThree);
SmallPrimesPow2LastThree = AllocateAndCopyULong(accelerator, DivisorGenerator.SmallPrimesPow2LastThree);
SmallPrimesLastNine = AllocateAndCopyUInt(accelerator, DivisorGenerator.SmallPrimesLastNine);
SmallPrimesPow2LastNine = AllocateAndCopyULong(accelerator, DivisorGenerator.SmallPrimesPow2LastNine);
SmallPrimesLastOneWithoutLastThree = AllocateAndCopyUInt(accelerator, DivisorGenerator.SmallPrimesLastOneWithoutLastThree);
SmallPrimesPow2LastOneWithoutLastThree = AllocateAndCopyULong(accelerator, DivisorGenerator.SmallPrimesPow2LastOneWithoutLastThree);
SmallPrimesLastSevenWithoutLastThree = AllocateAndCopyUInt(accelerator, DivisorGenerator.SmallPrimesLastSevenWithoutLastThree);
SmallPrimesPow2LastSevenWithoutLastThree = AllocateAndCopyULong(accelerator, DivisorGenerator.SmallPrimesPow2LastSevenWithoutLastThree);
SmallPrimesLastNineWithoutLastThree = AllocateAndCopyUInt(accelerator, DivisorGenerator.SmallPrimesLastNineWithoutLastThree);
SmallPrimesPow2LastNineWithoutLastThree = AllocateAndCopyULong(accelerator, DivisorGenerator.SmallPrimesPow2LastNineWithoutLastThree);
}
internal MemoryBuffer1D<uint, Stride1D.Dense> SmallPrimes { get; }
internal MemoryBuffer1D<ulong, Stride1D.Dense> SmallPrimesPow2 { get; }
internal MemoryBuffer1D<uint, Stride1D.Dense> SmallPrimesLastOne { get; }
internal MemoryBuffer1D<ulong, Stride1D.Dense> SmallPrimesPow2LastOne { get; }
internal MemoryBuffer1D<uint, Stride1D.Dense> SmallPrimesLastSeven { get; }
internal MemoryBuffer1D<ulong, Stride1D.Dense> SmallPrimesPow2LastSeven { get; }
internal MemoryBuffer1D<uint, Stride1D.Dense> SmallPrimesLastThree { get; }
internal MemoryBuffer1D<ulong, Stride1D.Dense> SmallPrimesPow2LastThree { get; }
internal MemoryBuffer1D<uint, Stride1D.Dense> SmallPrimesLastNine { get; }
internal MemoryBuffer1D<ulong, Stride1D.Dense> SmallPrimesPow2LastNine { get; }
internal MemoryBuffer1D<uint, Stride1D.Dense> SmallPrimesLastOneWithoutLastThree { get; }
internal MemoryBuffer1D<ulong, Stride1D.Dense> SmallPrimesPow2LastOneWithoutLastThree { get; }
internal MemoryBuffer1D<uint, Stride1D.Dense> SmallPrimesLastSevenWithoutLastThree { get; }
internal MemoryBuffer1D<ulong, Stride1D.Dense> SmallPrimesPow2LastSevenWithoutLastThree { get; }
internal MemoryBuffer1D<uint, Stride1D.Dense> SmallPrimesLastNineWithoutLastThree { get; }
internal MemoryBuffer1D<ulong, Stride1D.Dense> SmallPrimesPow2LastNineWithoutLastThree { get; }
public void Dispose()
{
SmallPrimes.Dispose();
SmallPrimesPow2.Dispose();
SmallPrimesLastOne.Dispose();
SmallPrimesPow2LastOne.Dispose();
SmallPrimesLastSeven.Dispose();
SmallPrimesPow2LastSeven.Dispose();
SmallPrimesLastThree.Dispose();
SmallPrimesPow2LastThree.Dispose();
SmallPrimesLastNine.Dispose();
SmallPrimesPow2LastNine.Dispose();
SmallPrimesLastOneWithoutLastThree.Dispose();
SmallPrimesPow2LastOneWithoutLastThree.Dispose();
SmallPrimesLastSevenWithoutLastThree.Dispose();
SmallPrimesPow2LastSevenWithoutLastThree.Dispose();
SmallPrimesLastNineWithoutLastThree.Dispose();
SmallPrimesPow2LastNineWithoutLastThree.Dispose();
}
private static MemoryBuffer1D<uint, Stride1D.Dense> AllocateAndCopyUInt(Accelerator accelerator, uint[] source)
{
var buffer = accelerator.Allocate1D<uint>(source.Length);
if (source.Length > 0)
{
buffer.View.CopyFromCPU(source);
}
return buffer;
}
private static MemoryBuffer1D<ulong, Stride1D.Dense> AllocateAndCopyULong(Accelerator accelerator, ulong[] source)
{
var buffer = accelerator.Allocate1D<ulong>(source.Length);
if (source.Length > 0)
{
buffer.View.CopyFromCPU(source);
}
return buffer;
}
}
private static readonly ConcurrentDictionary<Accelerator, DivisorGeneratorGpuTables> Cache = new(AcceleratorReferenceComparer.Instance);
public static void WarmUpByDivisorTables(Accelerator accelerator)
{
if (accelerator is null || accelerator.AcceleratorType == AcceleratorType.CPU)
{
return;
}
Cache.GetOrAdd(accelerator, acc => new DivisorGeneratorGpuTables(acc));
}
public static void Clear(Accelerator accelerator)
{
if (accelerator is null)
{
return;
}
if (Cache.TryRemove(accelerator, out var tables))
{
tables.Dispose();
}
}
public static void DisposeAll()
{
foreach (var entry in Cache)
{
entry.Value.Dispose();
}
Cache.Clear();
}
}
@@ -1,4 +1,5 @@
using System.Runtime.CompilerServices;
using PerfectNumbers.Core;
namespace PerfectNumbers.Core.Gpu;
@@ -23,14 +24,17 @@ internal struct ExponentRemainderStepperGpu
_currentResidue = GpuUInt128.One;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public readonly bool MatchesDivisor(in GpuDivisorPartialData divisor) => _modulus == divisor.Modulus;
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public bool MatchesDivisor(in GpuDivisorPartialData divisor)
{
return _modulus == divisor.Modulus;
}
/// <summary>
/// Clears the cached residue so the stepper can be reused for another divisor.
/// Callers must reinitialize the stepper before consuming any residues after a reset.
/// </summary>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
/// <summary>
/// Clears the cached residue so the stepper can be reused for another divisor.
/// Callers must reinitialize the stepper before consuming any residues after a reset.
/// </summary>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public void Reset()
{
PreviousExponent = 0UL;
+117
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@@ -0,0 +1,117 @@
using System;
using System.Collections.Concurrent;
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
public static class GpuContextPool
{
// The pool intentionally skips pre-loading ProcessEightBitWindows kernels so accelerator initialization
// stays stable; GpuKernelPool JIT-compiles them on first use alongside the small-cycle uploads.
// Default device preference for generic GPU kernels (prime scans, NTT, etc.)
internal sealed class PooledContext
{
public Context Context { get; }
public Accelerator Accelerator { get; }
public PooledContext()
{
Context = Context.CreateDefault();
Accelerator = Context.GetPreferredDevice(false).CreateAccelerator(Context);
DivisorGeneratorGpuCache.WarmUpByDivisorTables(Accelerator);
// NOTE: Avoid loading/compiling any kernel here to prevent implicit
// CL stream/queue creation during accelerator construction.
// Some OpenCL drivers are fragile when a queue is created immediately
// after device init. Real kernels will be JIT-loaded at first use.
}
public void Dispose()
{
// Ensure all cached GPU buffers for this accelerator are released.
NttGpuMath.ClearCaches(Accelerator);
// Release PrimeTester GPU state for this accelerator (kernel/device primes)
// Clear any per-accelerator cached resources to avoid releasing
// after the accelerator is destroyed.
DivisorGeneratorGpuCache.Clear(Accelerator);
PrimeTester.ClearGpuCaches(Accelerator);
Accelerator.Dispose();
Context.Dispose();
}
}
private static readonly ConcurrentQueue<PooledContext> GpuPool = new();
private static int WarmedGpuContextCount;
// Allows callers to choose CPU/GPU per use-case, decoupled from ForceCpu.
public static GpuContextLease Rent()
{
if (GpuPool.TryDequeue(out var gpu))
{
return new GpuContextLease(gpu);
}
// Create a new accelerator when the pool does not have one available.
return new GpuContextLease(new PooledContext());
}
public static void WarmUpPool(int threadCount)
{
if (threadCount <= WarmedGpuContextCount)
{
return;
}
int toCreate = threadCount - WarmedGpuContextCount;
var contexts = new PooledContext[toCreate];
for (int i = 0; i < toCreate; i++)
{
contexts[i] = new PooledContext();
}
for (int i = 0; i < toCreate; i++)
{
GpuPool.Enqueue(contexts[i]);
}
WarmedGpuContextCount = threadCount;
}
public static void DisposeAll()
{
while (GpuPool.TryDequeue(out var gpu))
{
gpu.Dispose();
}
DivisorGeneratorGpuCache.DisposeAll();
PrimeTester.DisposeGpuContexts();
WarmedGpuContextCount = 0;
}
private static void Return(PooledContext ctx)
{
ctx.Accelerator.Synchronize();
GpuPool.Enqueue(ctx);
}
public readonly struct GpuContextLease
{
private readonly PooledContext _ctx;
internal GpuContextLease(PooledContext ctx)
{
_ctx = ctx;
}
public readonly Context Context => _ctx.Context;
public readonly Accelerator Accelerator => _ctx.Accelerator;
public readonly void Dispose()
{
Return(_ctx);
}
}
}
+153
View File
@@ -0,0 +1,153 @@
using System;
using System.Collections.Concurrent;
using ILGPU;
using ILGPU.Runtime;
using static PerfectNumbers.Core.Gpu.GpuContextPool;
namespace PerfectNumbers.Core.Gpu;
public sealed class GpuKernelLease
{
private static readonly ConcurrentQueue<GpuKernelLease> Pool = new();
private Action? _releaseLimiter;
private GpuContextLease? _gpu;
private KernelContainer? _kernels;
private AcceleratorStream? _stream;
private GpuKernelLease()
{
}
internal static GpuKernelLease Rent(GpuPrimeWorkLimiter.Lease limiter, GpuContextLease gpu, KernelContainer kernels)
{
if (!Pool.TryDequeue(out var lease))
{
lease = new GpuKernelLease();
}
lease._releaseLimiter = limiter.Dispose;
lease._gpu = gpu;
lease._kernels = kernels;
lease._stream = null;
return lease;
}
public Accelerator Accelerator => _gpu?.Accelerator ?? throw new NullReferenceException("GPU context is already released");
public AcceleratorStream Stream
{
get
{
if (_stream is { } stream)
{
return stream;
}
// It feels that we can combine these into 1 return statement, but that increases the max stack frame size to 3 from 2
stream = Accelerator.CreateStream();
_stream = stream;
return stream;
}
}
public Action<AcceleratorStream, Index1D, ulong, ulong, ArrayView<GpuUInt128>, ArrayView<ulong>> OrderKernel
{
get
{
var accel = Accelerator; // avoid capturing 'this' in lambda
return KernelContainer.InitOnce(ref _kernels!.Order, () =>
{
var loaded = accel.LoadAutoGroupedStreamKernel<Index1D, ulong, ulong, ArrayView<GpuUInt128>, ArrayView<ulong>>(OrderKernels.OrderKernelScan);
var kernel = KernelUtil.GetKernel(loaded);
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, ulong, ArrayView<GpuUInt128>, ArrayView<ulong>>>();
});
}
}
public Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>> Pow2ModKernel
{
get
{
var accel = Accelerator;
return KernelContainer.InitOnce(ref _kernels!.Pow2Mod, () =>
{
var loaded = accel.LoadAutoGroupedStreamKernel<Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>(Pow2ModKernels.Pow2ModKernelScan);
var kernel = KernelUtil.GetKernel(loaded);
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>>();
});
}
}
public Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ulong, ulong, ulong, ulong, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>> IncrementalKernel
{
get
{
var accel = Accelerator;
return KernelContainer.InitOnce(ref _kernels!.Incremental, () =>
{
var loaded = accel.LoadAutoGroupedStreamKernel<Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ulong, ulong, ulong, ulong, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>>(IncrementalKernels.IncrementalKernelScan);
var kernel = KernelUtil.GetKernel(loaded);
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ulong, ulong, ulong, ulong, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>>>();
});
}
}
public Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<int>, ArrayView1D<ulong, Stride1D.Dense>> IncrementalOrderKernel
{
get
{
var accel = Accelerator;
return KernelContainer.InitOnce(ref _kernels!.IncrementalOrder, () =>
{
var loaded = accel.LoadAutoGroupedStreamKernel<Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<int>, ArrayView1D<ulong, Stride1D.Dense>>(IncrementalKernels.IncrementalOrderKernelScan);
var kernel = KernelUtil.GetKernel(loaded);
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<int>, ArrayView1D<ulong, Stride1D.Dense>>>();
});
}
}
public Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<int>, ArrayView1D<ulong, Stride1D.Dense>> Pow2ModOrderKernel
{
get
{
var accel = Accelerator;
return KernelContainer.InitOnce(ref _kernels!.Pow2ModOrder, () =>
{
var loaded = accel.LoadAutoGroupedStreamKernel<Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<int>, ArrayView1D<ulong, Stride1D.Dense>>(Pow2ModKernels.Pow2ModOrderKernelScan);
var kernel = KernelUtil.GetKernel(loaded);
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<int>, ArrayView1D<ulong, Stride1D.Dense>>>();
});
}
}
public Action<AcceleratorStream, Index1D, ulong, uint, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<int, Stride1D.Dense>, ArrayView1D<int, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>> SmallPrimeFactorKernel
{
get
{
var accel = Accelerator;
return KernelContainer.InitOnce(ref _kernels!.SmallPrimeFactor, () =>
{
var loaded = accel.LoadAutoGroupedStreamKernel<Index1D, ulong, uint, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<int, Stride1D.Dense>, ArrayView1D<int, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>(SmallPrimeFactorKernels.SmallPrimeFactorKernelScan);
var kernel = KernelUtil.GetKernel(loaded);
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, uint, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<int, Stride1D.Dense>, ArrayView1D<int, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>>();
});
}
}
public void Dispose()
{
_stream?.Dispose();
_stream = null;
_gpu?.Dispose();
_gpu = null;
_releaseLimiter?.Invoke();
_releaseLimiter = null;
_kernels = null;
Pool.Enqueue(this);
}
}
+271 -200
View File
@@ -1,232 +1,303 @@
using System.Collections.Concurrent;
using ILGPU;
using ILGPU.Runtime;
using PerfectNumbers.Core.Gpu.Accelerators;
using static PerfectNumbers.Core.Gpu.GpuContextPool;
namespace PerfectNumbers.Core.Gpu;
public readonly struct ResidueAutomatonArgs
{
public readonly ulong Q0M10;
public readonly ulong Step10;
public readonly ulong Q0M8;
public readonly ulong Step8;
public readonly ulong Q0M3;
public readonly ulong Step3;
public readonly ulong Q0M5;
public readonly ulong Step5;
public ResidueAutomatonArgs(ulong q0m10, ulong step10, ulong q0m8, ulong step8, ulong q0m3, ulong step3, ulong q0m5, ulong step5)
{
Q0M10 = q0m10; Step10 = step10; Q0M8 = q0m8; Step8 = step8; Q0M3 = q0m3; Step3 = step3; Q0M5 = q0m5; Step5 = step5;
}
}
public sealed class KernelContainer
{
// Serializes first-time initialization of kernels/buffers per accelerator.
public Action<AcceleratorStream, Index1D, ulong, ulong, ArrayView<GpuUInt128>, ArrayView<ulong>>? Order;
public Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong,
ulong, ulong, ulong, ulong, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>>? Incremental;
public Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong,
ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>,
ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>,
ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>? Pow2Mod;
public Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong,
ResidueAutomatonArgs, ArrayView<int>, ArrayView1D<ulong, Stride1D.Dense>>? IncrementalOrder;
public Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong,
ResidueAutomatonArgs, ArrayView<int>, ArrayView1D<ulong, Stride1D.Dense>>? Pow2ModOrder;
public Action<AcceleratorStream, Index1D, ulong, uint, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<int, Stride1D.Dense>, ArrayView1D<int, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>? SmallPrimeFactor;
// Optional device buffer with small divisor cycles (<= 4M). Index = divisor, value = cycle length.
public MemoryBuffer1D<ulong, Stride1D.Dense>? SmallCycles;
public MemoryBuffer1D<uint, Stride1D.Dense>? SmallPrimeFactorsPrimes;
public MemoryBuffer1D<ulong, Stride1D.Dense>? SmallPrimeFactorsSquares;
public MemoryBuffer1D<ulong, Stride1D.Dense>? SmallPrimeFactorPrimeSlots;
public MemoryBuffer1D<int, Stride1D.Dense>? SmallPrimeFactorExponentSlots;
public MemoryBuffer1D<int, Stride1D.Dense>? SmallPrimeFactorCountSlot;
public MemoryBuffer1D<ulong, Stride1D.Dense>? SmallPrimeFactorRemainingSlot;
public MemoryBuffer1D<uint, Stride1D.Dense>? SmallPrimesLastOne;
public MemoryBuffer1D<ulong, Stride1D.Dense>? SmallPrimesPow2LastOne;
public MemoryBuffer1D<uint, Stride1D.Dense>? SmallPrimesLastSeven;
public MemoryBuffer1D<ulong, Stride1D.Dense>? SmallPrimesPow2LastSeven;
public static T InitOnce<T>(ref T? slot, Func<T> factory) where T : class
{
var current = Volatile.Read(ref slot);
if (current is not null)
{
return current;
}
current = Volatile.Read(ref slot);
if (current is null)
{
current = factory();
Volatile.Write(ref slot, current);
}
return current;
}
}
public readonly struct ResiduePrimeViews(
ArrayView1D<uint, Stride1D.Dense> lastOne,
ArrayView1D<uint, Stride1D.Dense> lastSeven,
ArrayView1D<ulong, Stride1D.Dense> lastOnePow2,
ArrayView1D<ulong, Stride1D.Dense> lastSevenPow2)
{
public readonly ArrayView1D<uint, Stride1D.Dense> LastOne = lastOne;
public readonly ArrayView1D<uint, Stride1D.Dense> LastSeven = lastSeven;
public readonly ArrayView1D<ulong, Stride1D.Dense> LastOnePow2 = lastOnePow2;
public readonly ArrayView1D<ulong, Stride1D.Dense> LastSevenPow2 = lastSevenPow2;
}
public readonly struct SmallPrimeFactorTables
{
public readonly MemoryBuffer1D<uint, Stride1D.Dense> Primes;
public readonly MemoryBuffer1D<ulong, Stride1D.Dense> Squares;
public readonly int Count;
public SmallPrimeFactorTables(
MemoryBuffer1D<uint, Stride1D.Dense> primes,
MemoryBuffer1D<ulong, Stride1D.Dense> squares,
int count)
{
Primes = primes;
Squares = squares;
Count = count;
}
public ArrayView1D<uint, Stride1D.Dense> PrimesView => Primes.View;
public ArrayView1D<ulong, Stride1D.Dense> SquaresView => Squares.View;
}
public readonly struct SmallPrimeFactorScratch
{
public readonly MemoryBuffer1D<ulong, Stride1D.Dense> PrimeSlots;
public readonly MemoryBuffer1D<int, Stride1D.Dense> ExponentSlots;
public readonly MemoryBuffer1D<int, Stride1D.Dense> CountSlot;
public readonly MemoryBuffer1D<ulong, Stride1D.Dense> RemainingSlot;
public SmallPrimeFactorScratch(
MemoryBuffer1D<ulong, Stride1D.Dense> primeSlots,
MemoryBuffer1D<int, Stride1D.Dense> exponentSlots,
MemoryBuffer1D<int, Stride1D.Dense> countSlot,
MemoryBuffer1D<ulong, Stride1D.Dense> remainingSlot)
{
PrimeSlots = primeSlots;
ExponentSlots = exponentSlots;
CountSlot = countSlot;
RemainingSlot = remainingSlot;
}
public void Clear()
{
PrimeSlots.MemSetToZero();
ExponentSlots.MemSetToZero();
CountSlot.MemSetToZero();
RemainingSlot.MemSetToZero();
}
}
public class GpuKernelPool
{
[ThreadStatic]
private static KernelContainer[]? _pool;
private static readonly ConcurrentDictionary<Accelerator, KernelContainer> KernelCache = new(); // TODO: Replace this concurrent map with a simple accelerator-indexed lookup once kernel launchers are prewarmed during startup so we can drop the thread-safe wrapper entirely.
public static T InitOnce<T>(ref T? target, Func<T> valueFactory) where T : class
{
if (target is { } value)
{
return value;
}
private static KernelContainer GetKernels(Accelerator accelerator)
{
return KernelCache.GetOrAdd(accelerator, _ => new KernelContainer());
}
var newValue = valueFactory();
return Interlocked.CompareExchange(ref target, newValue, null) ?? newValue;
}
// Ensures the small cycles table is uploaded to the device for the given accelerator.
// Returns the ArrayView to pass into kernels (when kernels are extended to accept it).
public static ArrayView1D<ulong, Stride1D.Dense> EnsureSmallCyclesOnDevice(Accelerator accelerator)
{
var kernels = GetKernels(accelerator);
if (kernels.SmallCycles is { } buffer)
{
return buffer.View;
}
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
// Ensure single upload per accelerator even if multiple threads race here.
lock (kernels) // TODO: Remove this lock by pre-uploading the immutable small-cycle snapshot during initialization; once no mutation happens at runtime, the pool must expose a simple reference without synchronization.
{
if (kernels.SmallCycles is { } existing)
{
return existing.View;
}
var host = MersenneDivisorCycles.Shared.ExportSmallCyclesSnapshot(); // TODO: Preload this device buffer during startup and keep it immutable so we can delete the lock above in favor of the preloaded snapshot.
var device = accelerator.Allocate1D<ulong>(host.Length);
device.View.CopyFromCPU(host);
kernels.SmallCycles = device;
return device.View;
}
}
internal static KernelContainer GetOrAddKernels(int acceleratorIndex, AcceleratorStream stream, KernelType kernelType)
{
var pool = _pool ??= [];
if (pool[acceleratorIndex] is not { } kernels)
{
kernels = new();
}
public static ResiduePrimeViews EnsureSmallPrimesOnDevice(Accelerator accelerator)
{
var kernels = GetKernels(accelerator);
if (kernels.SmallPrimesLastOne is { } lastOne &&
kernels.SmallPrimesLastSeven is { } lastSeven &&
kernels.SmallPrimesPow2LastOne is { } lastOnePow2 &&
kernels.SmallPrimesPow2LastSeven is { } lastSevenPow2)
{
return new ResiduePrimeViews(lastOne.View, lastSeven.View, lastOnePow2.View, lastSevenPow2.View);
}
Accelerator accelerator = _accelerators[acceleratorIndex];
if (kernelType.HasFlag(KernelType.OrderKernelScan))
{
InitOrderKernelScan(accelerator, kernels);
}
lock (kernels) // TODO: Inline these small-prime uploads into startup initialization alongside the small-cycle snapshot so we can drop runtime locking and keep the GPU pool free of synchronization.
{
if (kernels.SmallPrimesLastOne is { } existingLastOne &&
kernels.SmallPrimesLastSeven is { } existingLastSeven &&
kernels.SmallPrimesPow2LastOne is { } existingLastOnePow2 &&
kernels.SmallPrimesPow2LastSeven is { } existingLastSevenPow2)
{
return new ResiduePrimeViews(existingLastOne.View, existingLastSeven.View, existingLastOnePow2.View, existingLastSevenPow2.View);
}
if (kernelType.HasFlag(KernelType.Pow2ModKernelScan))
{
InitPow2ModKernelScan(accelerator, kernels);
}
var hostLastOne = PrimesGenerator.SmallPrimesLastOne;
var hostLastSeven = PrimesGenerator.SmallPrimesLastSeven;
var hostLastOnePow2 = PrimesGenerator.SmallPrimesPow2LastOne;
var hostLastSevenPow2 = PrimesGenerator.SmallPrimesPow2LastSeven;
if (kernelType.HasFlag(KernelType.IncrementalKernelScan))
{
InitIncrementalKernelScan(accelerator, kernels);
}
var deviceLastOne = accelerator.Allocate1D<uint>(hostLastOne.Length);
deviceLastOne.View.CopyFromCPU(hostLastOne);
var deviceLastSeven = accelerator.Allocate1D<uint>(hostLastSeven.Length);
deviceLastSeven.View.CopyFromCPU(hostLastSeven);
var deviceLastOnePow2 = accelerator.Allocate1D<ulong>(hostLastOnePow2.Length);
deviceLastOnePow2.View.CopyFromCPU(hostLastOnePow2);
var deviceLastSevenPow2 = accelerator.Allocate1D<ulong>(hostLastSevenPow2.Length);
deviceLastSevenPow2.View.CopyFromCPU(hostLastSevenPow2);
if (kernelType.HasFlag(KernelType.IncrementalOrderKernelScan))
{
IncrementalOrderKernelScan(accelerator, kernels);
}
kernels.SmallPrimesLastOne = deviceLastOne;
kernels.SmallPrimesLastSeven = deviceLastSeven;
kernels.SmallPrimesPow2LastOne = deviceLastOnePow2;
kernels.SmallPrimesPow2LastSeven = deviceLastSevenPow2;
if (kernelType.HasFlag(KernelType.Pow2ModOrderKernelScan))
{
InitPow2ModOrderKernelScan(accelerator, kernels);
}
return new ResiduePrimeViews(deviceLastOne.View, deviceLastSeven.View, deviceLastOnePow2.View, deviceLastSevenPow2.View);
}
}
PreloadStaticTables(accelerator, kernels, stream, kernelType);
public static SmallPrimeFactorTables EnsureSmallPrimeFactorTables(Accelerator accelerator)
{
var kernels = GetKernels(accelerator);
if (kernels.SmallPrimeFactorsPrimes is { } primeBuffer && kernels.SmallPrimeFactorsSquares is { } squareBuffer)
{
return new SmallPrimeFactorTables(primeBuffer, squareBuffer, (int)primeBuffer.Length);
}
pool[acceleratorIndex] = kernels;
return kernels;
lock (kernels)
{
if (kernels.SmallPrimeFactorsPrimes is { } existingPrimes && kernels.SmallPrimeFactorsSquares is { } existingSquares)
{
return new SmallPrimeFactorTables(existingPrimes, existingSquares, (int)existingPrimes.Length);
}
static void InitOrderKernelScan(Accelerator accelerator, KernelContainer kernels)
{
InitOnce(ref kernels.Order, () =>
{
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ulong, ulong, ArrayView<GpuUInt128>, ArrayView<ulong>>(OrderKernels.OrderKernelScan);
var hostPrimes = PrimesGenerator.SmallPrimes;
var hostSquares = PrimesGenerator.SmallPrimesPow2;
var kernel = KernelUtil.GetKernel(loaded);
var devicePrimes = accelerator.Allocate1D<uint>(hostPrimes.Length);
devicePrimes.View.CopyFromCPU(hostPrimes);
var deviceSquares = accelerator.Allocate1D<ulong>(hostSquares.Length);
deviceSquares.View.CopyFromCPU(hostSquares);
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, ulong, ArrayView<GpuUInt128>, ArrayView<ulong>>>();
});
}
kernels.SmallPrimeFactorsPrimes = devicePrimes;
kernels.SmallPrimeFactorsSquares = deviceSquares;
static void InitPow2ModKernelScan(Accelerator accelerator, KernelContainer kernels)
{
InitOnce(ref kernels.Pow2Mod, () =>
{
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>(Pow2ModKernels.Pow2ModKernelScan);
return new SmallPrimeFactorTables(devicePrimes, deviceSquares, hostPrimes.Length);
}
}
var kernel = KernelUtil.GetKernel(loaded);
public static SmallPrimeFactorScratch EnsureSmallPrimeFactorScratch(Accelerator accelerator, int slotCount)
{
var kernels = GetKernels(accelerator);
lock (kernels)
{
MemoryBuffer1D<ulong, Stride1D.Dense>? primeSlots = kernels.SmallPrimeFactorPrimeSlots;
if (primeSlots is null || primeSlots.Length < slotCount)
{
primeSlots?.Dispose();
primeSlots = accelerator.Allocate1D<ulong>(slotCount);
kernels.SmallPrimeFactorPrimeSlots = primeSlots;
}
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>>();
});
}
MemoryBuffer1D<int, Stride1D.Dense>? exponentSlots = kernels.SmallPrimeFactorExponentSlots;
if (exponentSlots is null || exponentSlots.Length < slotCount)
{
exponentSlots?.Dispose();
exponentSlots = accelerator.Allocate1D<int>(slotCount);
kernels.SmallPrimeFactorExponentSlots = exponentSlots;
}
static void InitIncrementalKernelScan(Accelerator accelerator, KernelContainer kernels)
{
InitOnce(ref kernels.Incremental, () =>
{
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ulong, ulong, ulong, ulong, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>>(IncrementalKernels.IncrementalKernelScan);
MemoryBuffer1D<int, Stride1D.Dense>? countSlot = kernels.SmallPrimeFactorCountSlot;
if (countSlot is null)
{
countSlot = accelerator.Allocate1D<int>(1);
kernels.SmallPrimeFactorCountSlot = countSlot;
}
var kernel = KernelUtil.GetKernel(loaded);
MemoryBuffer1D<ulong, Stride1D.Dense>? remainingSlot = kernels.SmallPrimeFactorRemainingSlot;
if (remainingSlot is null)
{
remainingSlot = accelerator.Allocate1D<ulong>(1);
kernels.SmallPrimeFactorRemainingSlot = remainingSlot;
}
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ulong, ulong, ulong, ulong, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>>>();
});
}
return new SmallPrimeFactorScratch(primeSlots!, exponentSlots!, countSlot!, remainingSlot!);
}
}
static void IncrementalOrderKernelScan(Accelerator accelerator, KernelContainer kernels)
{
InitOnce(ref kernels.IncrementalOrder, () =>
{
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<int>, ArrayView1D<ulong, Stride1D.Dense>>(IncrementalKernels.IncrementalOrderKernelScan);
public static GpuKernelLease GetKernel(bool useGpuOrder)
{
var limiter = GpuPrimeWorkLimiter.Acquire();
var gpu = Rent();
var accelerator = gpu.Accelerator;
var kernels = GetKernels(accelerator);
return GpuKernelLease.Rent(limiter, gpu, kernels);
}
var kernel = KernelUtil.GetKernel(loaded);
/// <summary>
/// Runs a GPU action with an acquired accelerator and stream.
/// </summary>
/// <param name="action">Action to run with (Accelerator, Stream).</param>
public static void Run(Action<Accelerator, AcceleratorStream> action)
{
var lease = GetKernel(useGpuOrder: true);
var accelerator = lease.Accelerator;
var stream = accelerator.CreateStream();
action(accelerator, stream);
stream.Dispose();
lease.Dispose();
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte,
ulong, ResidueAutomatonArgs, ArrayView<int>, ArrayView1D<ulong, Stride1D.Dense>>>();
});
}
static void InitPow2ModOrderKernelScan(Accelerator accelerator, KernelContainer kernels)
{
InitOnce(ref kernels.Pow2ModOrder, () =>
{
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<int>, ArrayView1D<ulong, Stride1D.Dense>>(Pow2ModKernels.Pow2ModOrderKernelScan);
var kernel = KernelUtil.GetKernel(loaded);
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<int>, ArrayView1D<ulong, Stride1D.Dense>>>();
});
}
}
internal static void PreloadStaticTables(Accelerator accelerator, KernelContainer kernels, AcceleratorStream stream, KernelType kernelType)
{
if (kernelType.HasFlag(KernelType.SmallCycles))
{
EnsureSmallCyclesOnDevice(accelerator, kernels, stream);
}
if (kernelType.HasFlag(KernelType.SmallPrimes))
{
EnsureSmallPrimesOnDevice(accelerator, kernels, stream);
}
}
public static ArrayView1D<ulong, Stride1D.Dense> GetSmallCyclesOnDevice(KernelContainer kernels) => kernels.SmallCycles!;
// Ensures the small cycles table is uploaded to the device for the given accelerator.
// Returns the ArrayView to pass into kernels (when kernels are extended to accept it).
private static void EnsureSmallCyclesOnDevice(Accelerator accelerator, KernelContainer kernels, AcceleratorStream stream)
{
if (kernels.SmallCycles is { })
{
return;
}
var host = MersenneDivisorCycles.Shared.ExportSmallCyclesSnapshot();
MemoryBuffer1D<ulong, Stride1D.Dense>? device;
lock (accelerator)
{
device = accelerator.Allocate1D<ulong>(host.Length);
}
device.View.CopyFromCPU(stream, host);
kernels.SmallCycles = device;
}
public static ResiduePrimeViews GetSmallPrimesOnDevice(KernelContainer kernels) => new(
kernels.SmallPrimesLastOne!,
kernels.SmallPrimesLastSeven!,
kernels.SmallPrimesPow2LastOne!,
kernels.SmallPrimesPow2LastSeven!
);
private static void EnsureSmallPrimesOnDevice(Accelerator accelerator, KernelContainer kernels, AcceleratorStream stream)
{
if (kernels.SmallPrimesLastOne is { } &&
kernels.SmallPrimesLastSeven is { } &&
kernels.SmallPrimesPow2LastOne is { } &&
kernels.SmallPrimesPow2LastSeven is { })
{
return;
}
if (kernels.SmallPrimesLastOne is { } &&
kernels.SmallPrimesLastSeven is { } &&
kernels.SmallPrimesPow2LastOne is { } &&
kernels.SmallPrimesPow2LastSeven is { })
{
return;
}
var hostLastOne = PrimesGenerator.SmallPrimesLastOne;
var hostLastSeven = PrimesGenerator.SmallPrimesLastSeven;
var hostLastOnePow2 = PrimesGenerator.SmallPrimesPow2LastOne;
var hostLastSevenPow2 = PrimesGenerator.SmallPrimesPow2LastSeven;
MemoryBuffer1D<uint, Stride1D.Dense>? deviceLastOne;
MemoryBuffer1D<uint, Stride1D.Dense>? deviceLastSeven;
MemoryBuffer1D<ulong, Stride1D.Dense>? deviceLastOnePow2;
MemoryBuffer1D<ulong, Stride1D.Dense>? deviceLastSevenPow2;
lock (accelerator)
{
deviceLastOne = accelerator.Allocate1D<uint>(hostLastOne.Length);
deviceLastSeven = accelerator.Allocate1D<uint>(hostLastSeven.Length);
deviceLastOnePow2 = accelerator.Allocate1D<ulong>(hostLastOnePow2.Length);
deviceLastSevenPow2 = accelerator.Allocate1D<ulong>(hostLastSevenPow2.Length);
}
deviceLastOne.View.CopyFromCPU(stream, hostLastOne);
deviceLastSeven.View.CopyFromCPU(stream, hostLastSeven);
deviceLastOnePow2.View.CopyFromCPU(stream, hostLastOnePow2);
deviceLastSevenPow2.View.CopyFromCPU(stream, hostLastSevenPow2);
kernels.SmallPrimesLastOne = deviceLastOne;
kernels.SmallPrimesLastSeven = deviceLastSeven;
kernels.SmallPrimesPow2LastOne = deviceLastOnePow2;
kernels.SmallPrimesPow2LastSeven = deviceLastSevenPow2;
}
/// <summary>
/// Runs a GPU action with an acquired accelerator and stream.
/// </summary>
/// <param name="action">Action to run with (Accelerator, Stream).</param>
public static void Run(Action<Accelerator, AcceleratorStream> action)
{
// GpuPrimeWorkLimiter.Acquire();
var acceleratorIndex = AcceleratorPool.Shared.Rent();
var accelerator = _accelerators[acceleratorIndex];
var stream = AcceleratorStreamPool.Rent(acceleratorIndex);
action(accelerator, stream);
stream.Synchronize();
stream.Dispose();
accelerator.Dispose();
// GpuPrimeWorkLimiter.Release();
}
}
}
+32 -17
View File
@@ -2,29 +2,44 @@ namespace PerfectNumbers.Core.Gpu;
public static class GpuPrimeWorkLimiter
{
private static SemaphoreSlim _semaphore = new(1, int.MaxValue);
private static int _currentLimit = 1;
private static SemaphoreSlim _semaphore = new(1, int.MaxValue);
private static int _currentLimit = 1;
public static void Acquire() { } // => _semaphore.Wait();
public static void Release() { }// => _semaphore.Release();
public static void SetLimit(int value)
public static Lease Acquire()
{
if (value <= 0)
// TODO: Inline the pooled limiter guard from the GpuLimiterThroughputBenchmarks so prime-sieve
// GPU jobs stop allocating Lease instances on every acquisition.
var sem = _semaphore;
// sem.Wait();
return new Lease(sem);
}
public static void SetLimit(int value)
{
if (value == _currentLimit)
{
return;
}
// TODO: Switch to a shared limiter implementation with GpuWorkLimiter so we can coordinate CPU/GPU prime work using
// the same semaphore pool without reallocating per adjustment.
_semaphore = new SemaphoreSlim(value, value);
_currentLimit = value;
}
public sealed class Lease
{
private readonly SemaphoreSlim _sem;
internal Lease(SemaphoreSlim sem)
{
value = 1;
_sem = sem;
}
if (value == _currentLimit)
public void Dispose()
{
return;
// _sem.Release();
}
// TODO: Switch to a shared limiter implementation with GpuWorkLimiter so we can coordinate CPU/GPU prime work using
// the same semaphore pool without reallocating per adjustment.
var previous = _semaphore;
_semaphore = new SemaphoreSlim(value, value);
_currentLimit = value;
previous.Dispose();
}
}
+17 -47
View File
@@ -261,13 +261,13 @@ public struct GpuUInt128 : IComparable<GpuUInt128>, IEquatable<GpuUInt128>
public override readonly int GetHashCode() => HashCode.Combine(High, Low);
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public void Add(in ReadOnlyGpuUInt128 other) => Add(other.High, other.Low);
public void Add(in ReadOnlyGpuUInt128 other) => AddInternal(other.High, other.Low);
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public void Add(GpuUInt128 other) => Add(other.High, other.Low);
public void Add(GpuUInt128 other) => AddInternal(other.High, other.Low);
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public void Add(ulong otherHigh, ulong otherLow)
private void AddInternal(ulong otherHigh, ulong otherLow)
{
ulong originalLow = Low;
// We're reusing originalLow for carry to avoid an extra local.
@@ -316,7 +316,7 @@ public struct GpuUInt128 : IComparable<GpuUInt128>, IEquatable<GpuUInt128>
return;
}
Add(valueHigh, valueLow);
AddInternal(valueHigh, valueLow);
if (CompareTo(in modulus) >= 0)
{
Sub(in modulus);
@@ -589,6 +589,9 @@ public struct GpuUInt128 : IComparable<GpuUInt128>, IEquatable<GpuUInt128>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static GpuUInt128 BinaryGcd(GpuUInt128 u, GpuUInt128 v)
{
// TODO: Replace this scalar binary GCD with the branchless reduction from
// GpuUInt128BinaryGcdBenchmarks so CPU fallbacks stay aligned with the GPU kernel
// performance when resolving large divisor residues.
if (u.IsZero)
{
return v;
@@ -599,50 +602,26 @@ public struct GpuUInt128 : IComparable<GpuUInt128>, IEquatable<GpuUInt128>
return u;
}
ulong combinedLow = u.Low | v.Low;
int shift;
if (combinedLow != 0UL)
{
shift = BitOperations.TrailingZeroCount(combinedLow);
}
else
{
ulong combinedHigh = u.High | v.High;
shift = 64 + BitOperations.TrailingZeroCount(combinedHigh);
}
int shift = TrailingZeroCount(new GpuUInt128(u.High | v.High, u.Low | v.Low));
int zu = TrailingZeroCount(u);
u >>= zu;
GpuUInt128 currentV = v;
while (true)
do
{
int zv = TrailingZeroCount(currentV);
currentV >>= zv;
bool swap = u > currentV;
GpuUInt128 min = ConditionalSelect(u, currentV, swap);
GpuUInt128 max = ConditionalSelect(currentV, u, swap);
max.Sub(min);
if (max.IsZero)
int zv = TrailingZeroCount(v);
v >>= zv;
if (u > v)
{
return min << shift;
(u, v) = (v, u);
}
u = min;
currentV = max;
v -= u;
}
while (!v.IsZero);
return u << shift;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static GpuUInt128 ConditionalSelect(in GpuUInt128 left, in GpuUInt128 right, bool useRight)
{
ulong mask = useRight ? ulong.MaxValue : 0UL;
return new GpuUInt128(
left.High ^ ((left.High ^ right.High) & mask),
left.Low ^ ((left.Low ^ right.Low) & mask));
}
public void Sub(ulong value)
{
@@ -1550,15 +1529,6 @@ public struct GpuUInt128 : IComparable<GpuUInt128>, IEquatable<GpuUInt128>
high = hi;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public void Pow2()
{
ulong operand = Low;
Low = operand * operand;
ulong highProduct = operand * High;
High = highProduct + MulHigh(operand, operand);
}
}
// TODO: Check if the TODO below is still relevant.
@@ -0,0 +1,97 @@
using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
internal readonly struct HeuristicGpuDivisorTables
{
public static readonly HeuristicGpuDivisorTables Shared = default;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupADivisors;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorsEnding1;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorsEnding7;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorsEnding9;
public HeuristicGpuDivisorTables(
ArrayView1D<ulong, Stride1D.Dense> groupADivisors,
ArrayView1D<ulong, Stride1D.Dense> groupBDivisorsEnding1,
ArrayView1D<ulong, Stride1D.Dense> groupBDivisorsEnding7,
ArrayView1D<ulong, Stride1D.Dense> groupBDivisorsEnding9)
{
GroupADivisors = groupADivisors;
GroupBDivisorsEnding1 = groupBDivisorsEnding1;
GroupBDivisorsEnding7 = groupBDivisorsEnding7;
GroupBDivisorsEnding9 = groupBDivisorsEnding9;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ArrayView1D<ulong, Stride1D.Dense> SelectGroupB(byte ending)
{
return ending switch
{
1 => GroupBDivisorsEnding1,
7 => GroupBDivisorsEnding7,
9 => GroupBDivisorsEnding9,
_ => ArrayView1D<ulong, Stride1D.Dense>.Empty,
};
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ArrayView1D<ulong, Stride1D.Dense> SelectDivisors(HeuristicGpuDivisorTableKind kind, byte ending)
{
return kind switch
{
HeuristicGpuDivisorTableKind.GroupA => GroupADivisors,
HeuristicGpuDivisorTableKind.GroupBEnding1 => GroupBDivisorsEnding1,
HeuristicGpuDivisorTableKind.GroupBEnding7 => GroupBDivisorsEnding7,
HeuristicGpuDivisorTableKind.GroupBEnding9 => GroupBDivisorsEnding9,
_ => ArrayView1D<ulong, Stride1D.Dense>.Empty,
};
}
internal static void InitializeShared(in HeuristicGpuDivisorTables tables)
{
Unsafe.AsRef(in Shared) = tables;
}
}
internal readonly struct HeuristicGpuCombinedDivisorTables
{
public static readonly HeuristicGpuCombinedDivisorTables Shared = default;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorsEnding1;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorsEnding3;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorsEnding7;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorsEnding9;
public HeuristicGpuCombinedDivisorTables(
ArrayView1D<ulong, Stride1D.Dense> combinedDivisorsEnding1,
ArrayView1D<ulong, Stride1D.Dense> combinedDivisorsEnding3,
ArrayView1D<ulong, Stride1D.Dense> combinedDivisorsEnding7,
ArrayView1D<ulong, Stride1D.Dense> combinedDivisorsEnding9)
{
CombinedDivisorsEnding1 = combinedDivisorsEnding1;
CombinedDivisorsEnding3 = combinedDivisorsEnding3;
CombinedDivisorsEnding7 = combinedDivisorsEnding7;
CombinedDivisorsEnding9 = combinedDivisorsEnding9;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ArrayView1D<ulong, Stride1D.Dense> SelectCombined(byte ending)
{
return ending switch
{
1 => CombinedDivisorsEnding1,
3 => CombinedDivisorsEnding3,
7 => CombinedDivisorsEnding7,
9 => CombinedDivisorsEnding9,
_ => ArrayView1D<ulong, Stride1D.Dense>.Empty,
};
}
internal static void InitializeShared(in HeuristicGpuCombinedDivisorTables tables)
{
Unsafe.AsRef(in Shared) = tables;
}
}
@@ -1,58 +0,0 @@
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
public sealed class KernelContainer
{
// Serializes first-time initialization of kernels/buffers per accelerator.
public Action<AcceleratorStream, Index1D, ulong, ulong, ArrayView<GpuUInt128>, ArrayView<ulong>>? Order;
public Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong,
ulong, ulong, ulong, ulong, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>>? Incremental;
public Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong,
ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>,
ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>,
ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>? Pow2Mod;
public Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong,
ResidueAutomatonArgs, ArrayView<int>, ArrayView1D<ulong, Stride1D.Dense>>? IncrementalOrder;
public Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong,
ResidueAutomatonArgs, ArrayView<int>, ArrayView1D<ulong, Stride1D.Dense>>? Pow2ModOrder;
public Kernel? SmallPrimeFactor;
public Action<AcceleratorStream, Index1D, ulong, ArrayView1D<ulong, Stride1D.Dense>, int, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>? SpecialMax;
// Optional device buffer with small divisor cycles (<= 4M). Index = divisor, value = cycle length.
public MemoryBuffer1D<ulong, Stride1D.Dense>? SmallCycles;
public MemoryBuffer1D<uint, Stride1D.Dense>? SmallPrimesLastOne;
public MemoryBuffer1D<uint, Stride1D.Dense>? SmallPrimesLastSeven;
public MemoryBuffer1D<ulong, Stride1D.Dense>? SmallPrimesPow2LastOne;
public MemoryBuffer1D<ulong, Stride1D.Dense>? SmallPrimesPow2LastSeven;
public MemoryBuffer1D<uint, Stride1D.Dense>? SmallPrimeFactorsPrimes;
public MemoryBuffer1D<ulong, Stride1D.Dense>? SmallPrimeFactorsSquares;
public void Dispose()
{
// Order = null;
// Incremental = null;
// Pow2Mod = null;
// IncrementalOrder = null;
// Pow2ModOrder = null;
// SmallPrimeFactor = null;
// SpecialMax = null;
// SmallCycles?.Dispose();
// SmallPrimesLastOne?.Dispose();
// SmallPrimesLastSeven?.Dispose();
// SmallPrimesPow2LastOne?.Dispose();
// SmallPrimesPow2LastSeven?.Dispose();
// SmallPrimeFactorsPrimes?.Dispose();
// SmallPrimeFactorsSquares?.Dispose();
}
}
-14
View File
@@ -1,14 +0,0 @@
namespace PerfectNumbers.Core.Gpu;
[Flags]
public enum KernelType
{
None,
SmallCycles,
SmallPrimes,
Pow2ModKernelScan,
OrderKernelScan,
IncrementalKernelScan,
IncrementalOrderKernelScan,
Pow2ModOrderKernelScan
}
@@ -1,4 +1,7 @@
using ILGPU;
using ILGPU.Algorithms;
using ILGPU.Runtime;
using PerfectNumbers.Core;
namespace PerfectNumbers.Core.Gpu;
@@ -1,5 +1,6 @@
using ILGPU;
using ILGPU.Algorithms;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
@@ -1,4 +1,5 @@
using ILGPU;
using ILGPU.Algorithms;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
@@ -1,5 +1,7 @@
using System;
using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Runtime;
using UInt128 = System.UInt128;
namespace PerfectNumbers.Core.Gpu;
@@ -303,7 +305,7 @@ internal static class LucasLehmerKernels
states[idx] = s;
}
public static void Kernel(Index1D _, ulong exponent, GpuUInt128 modulus, ArrayView<GpuUInt128> state)
public static void Kernel(Index1D index, ulong exponent, GpuUInt128 modulus, ArrayView<GpuUInt128> state)
{
// Lucas–Lehmer iteration in the field GF(2^p-1).
// For p < 128, use a Mersenne-specific squaring + reduction to avoid
@@ -1,6 +1,5 @@
using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
@@ -33,7 +32,7 @@ internal static class NttBarrettKernels
}
// Barrett-based squaring: v = v^2 mod n for 128-bit n
public static void SquareBarrett128Kernel(Index1D index, AcceleratorStream stream, ArrayView<GpuUInt128> data, ulong modHigh, ulong modLow, ulong muHigh, ulong muLow)
public static void SquareBarrett128Kernel(Index1D index, ArrayView<GpuUInt128> data, ulong modHigh, ulong modLow, ulong muHigh, ulong muLow)
{
var v = data[index];
Mul128Full(v.High, v.Low, v.High, v.Low, out var z3, out var z2, out var z1, out var z0);
@@ -1,6 +1,5 @@
using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
@@ -44,7 +43,7 @@ internal static class NttMontgomeryKernels
data[index] = new GpuUInt128(0UL, v);
}
public static void SquareMont64Kernel(Index1D index, AcceleratorStream stream, ArrayView<GpuUInt128> data, ulong modulus, ulong nPrime)
public static void SquareMont64Kernel(Index1D index, ArrayView<GpuUInt128> data, ulong modulus, ulong nPrime)
{
ulong aR = data[index].Low;
ulong v = MontMul64(aR, aR, modulus, nPrime);
@@ -1,4 +1,5 @@
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
@@ -1,4 +1,5 @@
using ILGPU;
using ILGPU.Algorithms;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
@@ -1,80 +1,26 @@
using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Runtime;
using PerfectNumbers.Core;
namespace PerfectNumbers.Core.Gpu.Kernels;
namespace PerfectNumbers.Core.Gpu;
internal static class Pow2MontgomeryKernels
{
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static GpuUInt128 AdvancePolynomialGpu(GpuUInt128 x, ulong c, ulong modulus)
{
x.Pow2();
x.AddMod(c, modulus);
return x;
}
public static void Pow2MontgomeryKernelKeepMontgomery(
Index1D index,
ArrayView1D<ulong, Stride1D.Dense> exponents,
MontgomeryDivisorData divisor,
ArrayView1D<ulong, Stride1D.Dense> results)
{
results[index] = ULongExtensions.Pow2MontgomeryModWindowedGpuKeepMontgomery(divisor, exponents[index]);
}
public static void Pow2MontgomeryKernelKeepMontgomery(
Index1D index,
ArrayView1D<ulong, Stride1D.Dense> exponents,
MontgomeryDivisorData divisor,
ArrayView1D<ulong, Stride1D.Dense> results)
{
results[0] = ULongExtensions.Pow2MontgomeryModWindowedGpuKeepMontgomery(divisor, exponents[0]);
}
public static void Pow2MontgomeryKernelConvertToStandard(
Index1D index,
ArrayView1D<ulong, Stride1D.Dense> exponents,
MontgomeryDivisorData divisor,
ArrayView1D<ulong, Stride1D.Dense> results)
{
results[0] = ULongExtensions.Pow2MontgomeryModWindowedGpuConvertToStandard(divisor, exponents[0]);
}
public static void TryPollardRhoKernel(ulong n, int limit, ArrayView1D<ulong, Stride1D.Dense> randomState, ArrayView1D<byte, Stride1D.Dense> factored, ArrayView1D<ulong, Stride1D.Dense> factor)
{
factored[0] = 0;
if ((n & 1UL) == 0UL)
{
factor[0] = 2UL;
factored[0] = 1;
return;
}
int attempt = 0;
GpuUInt128 nGpuUInt128 = (GpuUInt128)n;
DeterministicRandomGpu random = new(randomState[0]);
while (attempt < limit)
{
ulong c = (random.NextUInt64() % (n - 1UL)) + 1UL;
GpuUInt128 x = (random.NextUInt64() % (n - 2UL)) + 2UL;
GpuUInt128 y = x;
GpuUInt128 d = GpuUInt128.One;
while (d.CompareTo(GpuUInt128.One) == 0)
{
x = AdvancePolynomialGpu(x, c, modulus: n);
y = AdvancePolynomialGpu(y, c, n);
y = AdvancePolynomialGpu(y, c, n);
GpuUInt128 diff = x.CompareTo(y) > 0 ? x - y : y - x;
d = GpuUInt128.BinaryGcd(diff, nGpuUInt128);
}
if (d != n)
{
if (d.High == 0)
{
factor[0] = d.Low;
factored[0] = 1;
return;
}
}
attempt++;
}
randomState[0] = random.State;
}
public static void Pow2MontgomeryKernelConvertToStandard(
Index1D index,
ArrayView1D<ulong, Stride1D.Dense> exponents,
MontgomeryDivisorData divisor,
ArrayView1D<ulong, Stride1D.Dense> results)
{
results[index] = ULongExtensions.Pow2MontgomeryModWindowedGpuConvertToStandard(divisor, exponents[index]);
}
}
File diff suppressed because it is too large. Load diff
@@ -1,79 +0,0 @@
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
internal static partial class PrimeOrderGpuHeuristics
{
internal static void EvaluateSpecialMaxCandidatesKernel(
Index1D index,
ulong phi,
ArrayView1D<ulong, Stride1D.Dense> factors,
int factorCount,
MontgomeryDivisorData divisor,
ArrayView1D<ulong, Stride1D.Dense> candidates,
ArrayView1D<ulong, Stride1D.Dense> resultOut)
{
if (index != 0)
{
return;
}
int actual = 0;
for (int i = 0; i < factorCount; i++)
{
ulong factor = factors[i];
if (factor <= 1UL)
{
continue;
}
ulong reduced = phi / factor;
if (reduced == 0UL)
{
continue;
}
candidates[actual] = reduced;
actual++;
}
if (actual == 0)
{
resultOut[0] = 1;
return;
}
for (int i = 1; i < actual; i++)
{
ulong current = candidates[i];
int insert = i - 1;
while (insert >= 0 && candidates[insert] > current)
{
candidates[insert + 1] = candidates[insert];
insert--;
}
candidates[insert + 1] = current;
}
var divisorPartial = new GpuDivisorPartialData(divisor.Modulus);
var stepper = new ExponentRemainderStepperGpu(divisorPartial);
if (stepper.InitializeIsUnityGpu(candidates[0]))
{
Atomic.Exchange(ref resultOut[0], 0);
return;
}
for (int i = 1; i < actual; i++)
{
if (stepper.ComputeNextIsUnityGpu(candidates[i]))
{
Atomic.Exchange(ref resultOut[0], 0);
return;
}
}
Atomic.Exchange(ref resultOut[0], 1);
}
}
@@ -2,39 +2,41 @@ using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Algorithms;
using ILGPU.Runtime;
using PerfectNumbers.Core.Gpu.Accelerators;
namespace PerfectNumbers.Core.Gpu;
public enum HeuristicGpuDivisorTableKind : byte
internal enum HeuristicGpuDivisorTableKind : byte
{
GroupA = 0,
GroupBEnding1 = 1,
GroupBEnding7 = 7,
GroupBEnding9 = 9,
Combined = 255,
}
internal static class PrimeTesterKernels
{
// GPU kernel: small-prime sieve only. Returns 1 if passes sieve (probable prime), 0 otherwise.
public static void SmallPrimeSieveKernel(
Index1D index,
ArrayView<ulong> numbers,
ArrayView<uint> smallPrimesLastOne,
ArrayView<uint> smallPrimesLastSeven,
ArrayView<uint> smallPrimesLastThree,
ArrayView<uint> smallPrimesLastNine,
ArrayView<ulong> smallPrimesPow2LastOne,
ArrayView<ulong> smallPrimesPow2LastSeven,
ArrayView<ulong> smallPrimesPow2LastThree,
ArrayView<ulong> smallPrimesPow2LastNine,
ArrayView<byte> results)
Index1D index,
ArrayView<ulong> numbers,
ArrayView<uint> smallPrimes,
ArrayView<uint> smallPrimesLastOne,
ArrayView<uint> smallPrimesLastSeven,
ArrayView<uint> smallPrimesLastThree,
ArrayView<uint> smallPrimesLastNine,
ArrayView<ulong> smallPrimesPow2,
ArrayView<ulong> smallPrimesPow2LastOne,
ArrayView<ulong> smallPrimesPow2LastSeven,
ArrayView<ulong> smallPrimesPow2LastThree,
ArrayView<ulong> smallPrimesPow2LastNine,
ArrayView<byte> results)
{
ulong n = numbers[index];
byte result = 1;
ArrayView<uint> primes;
ArrayView<ulong> primeSquares;
ArrayView<uint> primes = smallPrimes;
ArrayView<ulong> primeSquares = smallPrimesPow2;
ulong lastDigit = n % 10UL;
switch (lastDigit)
{
@@ -53,9 +55,7 @@ internal static class PrimeTesterKernels
case 9UL:
primes = smallPrimesLastNine;
primeSquares = smallPrimesPow2LastNine;
break;
default:
return;
break;
}
int length = (int)primes.Length;
@@ -78,66 +78,29 @@ internal static class PrimeTesterKernels
results[index] = result;
}
public static void HeuristicTrialCombinedDivisionKernel(
Index1D index,
byte nMod10,
ArrayView<int> resultFlag,
ulong n,
ulong maxDivisorSquare,
HeuristicCombinedGpuViews tables)
{
// byte nMod10 = (byte)(n % 10UL);
ArrayView1D<ulong, Stride1D.Dense> divisors = tables.SelectDivisors(nMod10);
ArrayView1D<ulong, Stride1D.Dense> divisorSquares = tables.SelectDivisorSquares(nMod10);
int divisorLength = (int)divisorSquares.Length;
int threadIndex = index;
if (threadIndex >= divisorLength)
{
return;
}
ulong divisorSquare = divisorSquares[threadIndex];
if (divisorSquare > maxDivisorSquare)
{
return;
}
ulong divisor = divisors[threadIndex];
divisor = n % divisor;
if (divisor == 0UL)
{
resultFlag[0] = 1;
}
}
public static void HeuristicTrialGroupABDivisionKernel(
public static void HeuristicTrialDivisionKernel(
Index1D index,
ArrayView<int> resultFlag,
ulong n,
ulong maxDivisorSquare,
ulong maxDivisor,
HeuristicGpuDivisorTableKind tableKind,
HeuristicGroupABGpuViews tables)
HeuristicGpuDivisorTables tables,
HeuristicGpuCombinedDivisorTables combinedTables)
{
ArrayView1D<ulong, Stride1D.Dense> divisors = tables.SelectDivisors(tableKind);
ArrayView1D<ulong, Stride1D.Dense> divisorSquares = tables.SelectDivisorSquares(tableKind);
byte nMod10 = (byte)(n % 10UL);
ArrayView1D<ulong, Stride1D.Dense> divisors = tableKind == HeuristicGpuDivisorTableKind.Combined
? combinedTables.SelectCombined(nMod10)
: tables.SelectDivisors(tableKind, nMod10);
int divisorLength = (int)divisorSquares.Length;
int divisorLength = (int)divisors.Length;
int threadIndex = index;
if (threadIndex >= divisorLength)
{
return;
}
bool skipThread = threadIndex >= divisorLength;
ulong divisor = skipThread ? 1UL : divisors[threadIndex];
skipThread = skipThread | (divisor > maxDivisor);
ulong divisorSquare = divisorSquares[threadIndex];
if (divisorSquare > maxDivisorSquare)
{
return;
}
ulong divisor = divisors[threadIndex];
divisor = n % divisor;
if (divisor == 0UL)
ulong remainder = skipThread ? 1UL : n % divisor;
bool hasFactor = !skipThread & (remainder == 0UL);
if (hasFactor)
{
resultFlag[0] = 1;
}
@@ -153,37 +116,35 @@ internal static class PrimeTesterKernels
private static ulong BinaryGcdGpu(ulong u, ulong v)
{
// TODO: Replace this inline GPU binary GCD with the kernel extracted from
// GpuUInt128BinaryGcdBenchmarks via GpuKernelPool so device callers reuse the
// fully unrolled ladder instead of this branchy fallback.
bool uIsZero = u == 0UL;
bool vIsZero = v == 0UL;
bool eitherZero = uIsZero | vIsZero;
ulong zeroResult = uIsZero ? v : u;
ulong combined = (u | v) | 1UL;
ulong combined = u | v | 1UL;
int shift = XMath.TrailingZeroCount(combined);
ulong currentU = u >> XMath.TrailingZeroCount(u | 1UL);
ulong currentV = v >> XMath.TrailingZeroCount(v | 1UL);
while (true)
ulong normalizedU = u >> XMath.TrailingZeroCount(u | 1UL);
ulong normalizedV = v >> XMath.TrailingZeroCount(v | 1UL);
ulong currentU = normalizedU;
ulong currentV = normalizedV;
bool loopCondition = currentV != 0UL;
while (loopCondition)
{
currentV >>= XMath.TrailingZeroCount(currentV);
bool swap = currentU > currentV;
ulong minValue = ConditionalSelect(currentU, currentV, swap);
ulong maxValue = ConditionalSelect(currentV, currentU, swap);
currentV = maxValue - minValue;
ulong minValue = XMath.Min(currentU, currentV);
ulong maxValue = XMath.Max(currentU, currentV);
currentU = minValue;
if (currentV == 0UL)
{
ulong gcd = currentU << shift;
return eitherZero ? zeroResult : gcd;
}
currentV = maxValue - minValue;
loopCondition = currentV != 0UL;
}
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static ulong ConditionalSelect(ulong left, ulong right, bool useRight)
{
ulong mask = useRight ? ulong.MaxValue : 0UL;
return left ^ ((left ^ right) & mask);
ulong gcd = currentU << shift;
return eitherZero ? zeroResult : gcd;
}
}
File diff suppressed because it is too large. Load diff
@@ -1,3 +1,4 @@
using System.Collections.Concurrent;
using ILGPU;
using ILGPU.Runtime;
@@ -8,157 +9,127 @@ namespace PerfectNumbers.Core.Gpu;
/// </summary>
public sealed class MersenneNumberDivisorGpuTester
{
[ThreadStatic]
private static Dictionary<Accelerator, Queue<MemoryBuffer1D<byte, Stride1D.Dense>>>? _resultBuffers;
private readonly ConcurrentDictionary<Accelerator, Action<Index1D, ulong, ReadOnlyGpuUInt128, ArrayView<byte>>> _kernelCache = new();
private readonly ConcurrentDictionary<Accelerator, MemoryBuffer1D<byte, Stride1D.Dense>> _resultBuffers = new();
private static Queue<MemoryBuffer1D<byte, Stride1D.Dense>> GetQueue(Accelerator accelerator)
{
var pool = _resultBuffers ??= [];
if (!pool.TryGetValue(accelerator, out var bufferQueue))
{
bufferQueue = [];
pool[accelerator] = bufferQueue;
}
private Action<Index1D, ulong, ReadOnlyGpuUInt128, ArrayView<byte>> GetKernel(Accelerator accelerator) =>
_kernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ulong, ReadOnlyGpuUInt128, ArrayView<byte>>(DivisorKernels.Kernel));
return bufferQueue;
}
public static void BuildDivisorCandidates()
{
ulong[] snapshot = MersenneDivisorCycles.Shared.ExportSmallCyclesSnapshot();
(ulong divisor, uint cycle)[] list = new (ulong divisor, uint cycle)[snapshot.Length / 2];
ulong cycle;
int count = 0, i, snapshotLength = snapshot.Length;
for (i = 3; i < snapshotLength; i += 2)
{
cycle = snapshot[i];
if (cycle == 0U)
{
continue;
}
private static Action<AcceleratorStream, Index1D, ulong, ReadOnlyGpuUInt128, ArrayView<byte>> GetDivisorKernel(Accelerator accelerator)
{
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ulong, ReadOnlyGpuUInt128, ArrayView<byte>>(DivisorKernels.Kernel);
list[count++] = ((ulong)i, (uint)cycle);
}
var kernel = KernelUtil.GetKernel(loaded);
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, ReadOnlyGpuUInt128, ArrayView<byte>>>();
}
public static void BuildDivisorCandidates()
{
ulong[] snapshot = MersenneDivisorCycles.Shared.ExportSmallCyclesSnapshot();
(ulong divisor, uint cycle)[] list = new (ulong divisor, uint cycle)[snapshot.Length / 2];
ulong cycle;
int count = 0, i, snapshotLength = snapshot.Length;
for (i = 3; i < snapshotLength; i += 2)
{
cycle = snapshot[i];
if (cycle == 0U)
{
continue;
}
list[count++] = ((ulong)i, (uint)cycle);
}
_divisorCandidates = count == 0 ? [] : list[..count];
}
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
public bool IsDivisible(ulong exponent, in ReadOnlyGpuUInt128 divisor)
{
// var accelerator = SharedGpuContext.CreateAccelerator();
var acceleratorIndex = AcceleratorPool.Shared.Rent();
var accelerator = _accelerators[acceleratorIndex];
var stream = accelerator.CreateStream();
Queue<MemoryBuffer1D<byte, Stride1D.Dense>> resultBuffers = GetQueue(accelerator);
if (!resultBuffers.TryDequeue(out var resultBuffer))
{
// lock(accelerator)
{
resultBuffer = accelerator.Allocate1D<byte>(1);
}
}
_divisorCandidates = count == 0 ? [] : list[..count];
}
public bool IsDivisible(ulong exponent, in ReadOnlyGpuUInt128 divisor)
{
var gpu = GpuContextPool.Rent();
var accelerator = gpu.Accelerator;
var kernel = GetKernel(accelerator);
var resultBuffer = _resultBuffers.GetOrAdd(accelerator, acc => acc.Allocate1D<byte>(1));
// There is no point in clearing this buffer. We always override item [0] and never use it beyond item [0]
// resultBuffer.MemSetToZero(stream);
var divisorKernel = GetDivisorKernel(accelerator);
divisorKernel(stream, 1, exponent, divisor, resultBuffer.View);
byte result = 0;
resultBuffer.View.CopyToCPU(stream, ref result, 1);
stream.Synchronize();
bool divisible = result != 0;
resultBuffers.Enqueue(resultBuffer);
stream.Dispose();
// AcceleratorPool.Shared.Return(accelerator);
// accelerator.Dispose();
return divisible;
}
// resultBuffer.MemSetToZero();
kernel(1, exponent, divisor, resultBuffer.View);
accelerator.Synchronize();
Span<byte> result = stackalloc byte[1];
resultBuffer.View.CopyToCPU(ref result[0], 1);
bool divisible = result[0] != 0;
result[0] = 0;
resultBuffer.View.CopyFromCPU(ref result[0], 1);
accelerator.Synchronize();
gpu.Dispose();
return divisible;
}
private static (ulong divisor, uint cycle)[]? _divisorCandidates = [];
private static (ulong divisor, uint cycle)[]? _divisorCandidates = Array.Empty<(ulong divisor, uint cycle)>();
public bool IsPrime(ulong p, UInt128 d, ulong divisorCyclesSearchLimit, out bool divisorsExhausted)
{
ReadOnlyGpuUInt128 readOnlyDivisor;
public bool IsPrime(ulong p, UInt128 d, ulong divisorCyclesSearchLimit, out bool divisorsExhausted)
{
ReadOnlyGpuUInt128 readOnlyDivisor;
if (d != UInt128.Zero)
{
readOnlyDivisor = new ReadOnlyGpuUInt128(d);
if (IsDivisible(p, in readOnlyDivisor))
{
divisorsExhausted = true;
return false;
}
if (d != UInt128.Zero)
{
readOnlyDivisor = new ReadOnlyGpuUInt128(d);
if (IsDivisible(p, in readOnlyDivisor))
{
divisorsExhausted = true;
return false;
}
divisorsExhausted = false;
return true;
}
divisorsExhausted = false;
return true;
}
if (_divisorCandidates is { Length: > 0 } candidates)
{
int candidateCount = candidates.Length;
for (int index = 0; index < candidateCount; index++)
{
(ulong candidateDivisor, uint cycle) = candidates[index];
if (p % cycle != 0UL)
{
continue;
}
if (_divisorCandidates is { Length: > 0 } candidates)
{
int candidateCount = candidates.Length;
for (int index = 0; index < candidateCount; index++)
{
(ulong candidateDivisor, uint cycle) = candidates[index];
if (p % cycle != 0UL)
{
continue;
}
readOnlyDivisor = new ReadOnlyGpuUInt128(candidateDivisor); // Reusing readOnlyDivisor for candidate divisors.
if (IsDivisible(p, in readOnlyDivisor))
{
divisorsExhausted = true;
return false;
}
}
}
readOnlyDivisor = new ReadOnlyGpuUInt128(candidateDivisor); // Reusing readOnlyDivisor for candidate divisors.
if (IsDivisible(p, in readOnlyDivisor))
{
divisorsExhausted = true;
return false;
}
}
}
UInt128 kMul2;
var divisorCycles = MersenneDivisorCycles.Shared;
UInt128 maxK2 = UInt128.MaxValue / ((UInt128)p << 1);
ulong limit = divisorCyclesSearchLimit;
if ((UInt128)limit > maxK2)
{
limit = (ulong)maxK2;
}
UInt128 kMul2;
var divisorCycles = MersenneDivisorCycles.Shared;
UInt128 maxK2 = UInt128.MaxValue / ((UInt128)p << 1);
ulong limit = divisorCyclesSearchLimit;
if ((UInt128)limit > maxK2)
{
limit = (ulong)maxK2;
}
for (ulong k2 = 1UL; k2 <= limit; k2++)
{
kMul2 = (UInt128)k2 << 1;
UInt128 candidate = checked(kMul2 * p);
d = checked(candidate + UInt128.One);
if (p < 64UL && d == ((UInt128)1 << (int)p) - UInt128.One)
{
continue;
}
for (ulong k2 = 1UL; k2 <= limit; k2++)
{
kMul2 = (UInt128)k2 << 1;
UInt128 candidate = checked(kMul2 * p);
d = checked(candidate + UInt128.One);
if (p < 64UL && d == ((UInt128)1 << (int)p) - UInt128.One)
{
continue;
}
UInt128 cycle128 = MersenneDivisorCycles.GetCycle(d);
if ((UInt128)p % cycle128 != UInt128.Zero)
{
continue;
}
UInt128 cycle128 = MersenneDivisorCycles.GetCycle(d);
if ((UInt128)p % cycle128 != UInt128.Zero)
{
continue;
}
readOnlyDivisor = new ReadOnlyGpuUInt128(d); // Reusing readOnlyDivisor for generated divisors.
if (IsDivisible(p, in readOnlyDivisor))
{
divisorsExhausted = true;
return false;
}
}
readOnlyDivisor = new ReadOnlyGpuUInt128(d); // Reusing readOnlyDivisor for generated divisors.
if (IsDivisible(p, in readOnlyDivisor))
{
divisorsExhausted = true;
return false;
}
}
divisorsExhausted = (UInt128)divisorCyclesSearchLimit >= maxK2;
return true;
}
divisorsExhausted = (UInt128)divisorCyclesSearchLimit >= maxK2;
return true;
}
}
@@ -12,41 +12,36 @@ public class MersenneNumberIncrementalGpuTester(GpuKernelType kernelType, bool u
private readonly GpuKernelType _kernelType = kernelType;
private readonly bool _useGpuOrder = useGpuOrder;
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
public void Scan(ulong exponent, UInt128 twoP, LastDigit lastDigit, UInt128 maxK, ref bool isPrime)
{
throw new NotImplementedException($"GPU incremental scanning requires the device cycle heuristics implementation (kernel: {_kernelType}, GPU order: {_useGpuOrder}).");
// GpuPrimeWorkLimiter.Acquire();
var acceleratorIndex = AcceleratorPool.Shared.Rent();
var accelerator = _accelerators[acceleratorIndex];
var stream = accelerator.CreateStream();
var gpuLease = GpuKernelPool.GetKernel(_useGpuOrder);
var accelerator = gpuLease.Accelerator;
var stream = gpuLease.Stream;
int batchSize = GpuConstants.ScanBatchSize; // large batch improves GPU occupancy
UInt128 kStart = 1UL;
ulong divMul = (ulong)((((UInt128)1 << 64) - UInt128.One) / exponent) + 1UL;
byte last = lastDigit == LastDigit.Seven ? (byte)1 : (byte)0; // ILGPU kernels do not support bool parameters
KernelContainer kernels = GpuKernelPool.GetOrAddKernels(acceleratorIndex, stream, KernelType.Pow2ModKernelScan | KernelType.IncrementalKernelScan);
var pow2Kernel = kernels.Pow2Mod!;
var incKernel = kernels.Incremental!;
var pow2Kernel = gpuLease.Pow2ModKernel;
var incKernel = gpuLease.IncrementalKernel;
ulong step10 = (exponent.Mod10() << 1).Mod10();
ulong step8 = ((exponent & 7UL) << 1) & 7UL;
ulong step3 = ((exponent % 3UL) << 1) % 3UL;
ulong step5 = ((exponent % 5UL) << 1) % 5UL;
GpuUInt128 twoPGpu = (GpuUInt128)twoP;
var smallCyclesView = GpuKernelPool.GetSmallCyclesOnDevice(kernels);
var smallCyclesView = GpuKernelPool.EnsureSmallCyclesOnDevice(accelerator);
ResiduePrimeViews primeViews = default;
if (_kernelType == GpuKernelType.Pow2Mod)
{
primeViews = GpuKernelPool.GetSmallPrimesOnDevice(kernels);
primeViews = GpuKernelPool.EnsureSmallPrimesOnDevice(accelerator);
}
var orderBuffer = accelerator.Allocate1D<ulong>(batchSize);
// Avoid giant stack allocations that can trigger StackOverflow when batchSize is large.
// Rent a reusable array from the shared pool instead.
ArrayPool<ulong> ulongPool = ThreadStaticPools.UlongPool;
ulong[] orderArray = ulongPool.Rent(batchSize);
// Avoid giant stack allocations that can trigger StackOverflow when batchSize is large.
// Rent a reusable array from the shared pool instead.
ulong[] orderArray = ArrayPool<ulong>.Shared.Rent(batchSize);
UInt128 remaining;
int currentSize;
int i;
@@ -97,8 +92,8 @@ public class MersenneNumberIncrementalGpuTester(GpuKernelType kernelType, bool u
smallCyclesView);
}
orderBuffer.View.CopyToCPU(stream, ref MemoryMarshal.GetReference(orders), currentSize);
stream.Synchronize();
orderBuffer.View.CopyToCPU(ref MemoryMarshal.GetReference(orders), currentSize);
if (_kernelType == GpuKernelType.Pow2Mod)
{
for (i = 0; i < currentSize; i++)
@@ -125,9 +120,8 @@ public class MersenneNumberIncrementalGpuTester(GpuKernelType kernelType, bool u
kStart += (UInt128)currentSize;
}
stream.Dispose();
ulongPool.Return(orderArray);
orderBuffer.Dispose();
// GpuPrimeWorkLimiter.Release();
ArrayPool<ulong>.Shared.Return(orderArray);
orderBuffer.Dispose();
gpuLease.Dispose();
}
}
@@ -8,125 +8,32 @@ namespace PerfectNumbers.Core.Gpu;
public class MersenneNumberLucasLehmerGpuTester
{
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ulong, GpuUInt128, ArrayView<GpuUInt128>>>? _lucasLehmerKernel;
private readonly ConcurrentDictionary<Accelerator, Action<Index1D, ulong, GpuUInt128, ArrayView<GpuUInt128>>> KernelCache = new();
private readonly ConcurrentDictionary<Accelerator, Action<Index1D, ulong, ArrayView<GpuUInt128>>> AddSmallKernelCache = new();
private readonly ConcurrentDictionary<Accelerator, Action<Index1D, ulong, ArrayView<GpuUInt128>>> SubSmallKernelCache = new();
private readonly ConcurrentDictionary<Accelerator, Action<Index1D, ulong, ArrayView<GpuUInt128>>> ReduceKernelCache = new();
private readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, ArrayView<byte>>> IsZeroKernelCache = new();
private readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<ulong>, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>>> BatchKernelCache = new();
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ulong, ArrayView<GpuUInt128>>>? _addSmallKernel;
private Action<Index1D, ulong, GpuUInt128, ArrayView<GpuUInt128>> GetKernel(Accelerator accelerator)
{
return KernelCache.GetOrAdd(accelerator, accel => accel.LoadAutoGroupedStreamKernel<Index1D, ulong, GpuUInt128, ArrayView<GpuUInt128>>(LucasLehmerKernels.Kernel));
}
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ulong, ArrayView<GpuUInt128>>>? _subSmallKernel;
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ulong, ArrayView<GpuUInt128>>>? _reduceKernel;
private Action<Index1D, ulong, ArrayView<GpuUInt128>> GetAddSmallKernel(Accelerator accelerator) =>
AddSmallKernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ulong, ArrayView<GpuUInt128>>(LucasLehmerKernels.AddSmallKernel));
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ArrayView<byte>>>? _isZeroKernel;
private Action<Index1D, ulong, ArrayView<GpuUInt128>> GetSubSmallKernel(Accelerator accelerator) =>
SubSmallKernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ulong, ArrayView<GpuUInt128>>(LucasLehmerKernels.SubtractSmallKernel));
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<ulong>, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>>>? _lucasLehmerBatchKernel;
private Action<Index1D, ulong, ArrayView<GpuUInt128>> GetReduceKernel(Accelerator accelerator) =>
ReduceKernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ulong, ArrayView<GpuUInt128>>(LucasLehmerKernels.ReduceModMersenneKernel));
private static Action<AcceleratorStream, Index1D, ulong, GpuUInt128, ArrayView<GpuUInt128>> GetLucasLehmerKernel(Accelerator accelerator)
{
var pool = _lucasLehmerKernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
private Action<Index1D, ArrayView<GpuUInt128>, ArrayView<byte>> GetIsZeroKernel(Accelerator accelerator) =>
IsZeroKernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ArrayView<byte>>(LucasLehmerKernels.IsZeroKernel));
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ulong, GpuUInt128, ArrayView<GpuUInt128>>(LucasLehmerKernels.Kernel);
var kernel = KernelUtil.GetKernel(loaded);
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, GpuUInt128, ArrayView<GpuUInt128>>>();
pool[accelerator] = cached;
return cached;
}
private static Action<AcceleratorStream, Index1D, ulong, ArrayView<GpuUInt128>> GetAddSmallKernel(Accelerator accelerator)
{
var pool = _addSmallKernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ulong, ArrayView<GpuUInt128>>(LucasLehmerKernels.AddSmallKernel);
var kernel = KernelUtil.GetKernel(loaded);
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, ArrayView<GpuUInt128>>>();
pool[accelerator] = cached;
return cached;
}
private static Action<AcceleratorStream, Index1D, ulong, ArrayView<GpuUInt128>> GetSubSmallKernel(Accelerator accelerator)
{
var pool = _subSmallKernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ulong, ArrayView<GpuUInt128>>(LucasLehmerKernels.SubtractSmallKernel);
var kernel = KernelUtil.GetKernel(loaded);
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, ArrayView<GpuUInt128>>>();
pool[accelerator] = cached;
return cached;
}
private static Action<AcceleratorStream, Index1D, ulong, ArrayView<GpuUInt128>> GetReduceKernel(Accelerator accelerator)
{
var pool = _reduceKernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ulong, ArrayView<GpuUInt128>>(LucasLehmerKernels.ReduceModMersenneKernel);
var kernel = KernelUtil.GetKernel(loaded);
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, ArrayView<GpuUInt128>>>();
pool[accelerator] = cached;
return cached;
}
private static Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ArrayView<byte>> GetIsZeroKernel(Accelerator accelerator)
{
var pool = _isZeroKernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ArrayView<byte>>(LucasLehmerKernels.IsZeroKernel);
var kernel = KernelUtil.GetKernel(loaded);
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ArrayView<byte>>>();
pool[accelerator] = cached;
return cached;
}
private static Action<AcceleratorStream, Index1D, ArrayView<ulong>, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>> GetLucasLehmerBatchKernel(Accelerator accelerator)
{
var pool = _lucasLehmerBatchKernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<ulong>, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>>(LucasLehmerKernels.KernelBatch);
var kernel = KernelUtil.GetKernel(loaded);
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<ulong>, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>>>();
pool[accelerator] = cached;
return cached;
}
private Action<Index1D, ArrayView<ulong>, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>> GetBatchKernel(Accelerator accelerator) =>
BatchKernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<ulong>, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>>(LucasLehmerKernels.KernelBatch));
// Configurable LL slice size to keep kernels short. Default 32.
public int SliceSize = 32;
@@ -147,11 +54,13 @@ public class MersenneNumberLucasLehmerGpuTester
return false;
}
var limiter = GpuPrimeWorkLimiter.Acquire();
bool result;
if (exponent >= 128UL)
{
if (!TryGetNttParameters(exponent, out var nttMod, out var primitiveRoot))
{
limiter.Dispose();
throw new NotSupportedException("NTT parameters for the given exponent are not available.");
}
@@ -159,22 +68,19 @@ public class MersenneNumberLucasLehmerGpuTester
}
else
{
// GpuPrimeWorkLimiter.Acquire();
var acceleratorIndex = AcceleratorPool.Shared.Rent();
var accelerator = _accelerators[acceleratorIndex];
var stream = accelerator.CreateStream();
var gpu = GpuContextPool.Rent();
var accelerator = gpu.Accelerator;
var kernel = GetKernel(accelerator);
var modulus = new GpuUInt128(((UInt128)1 << (int)exponent) - 1UL); // TODO: Cache these Mersenne moduli per exponent so LL GPU runs skip rebuilding them every launch.
var buffer = accelerator.Allocate1D<GpuUInt128>(1);
var lucasLehmerKernel = GetLucasLehmerKernel(accelerator);
lucasLehmerKernel(stream, 1, exponent, modulus, buffer.View);
stream.Synchronize();
// TODO: Replace this with .CopyToCPU with pre-allocated buffer using stream. Synchronize on the stream after copy.
var buffer = accelerator.Allocate1D<GpuUInt128>(1);
kernel(1, exponent, modulus, buffer.View);
accelerator.Synchronize();
result = buffer.GetAsArray1D()[0].IsZero;
buffer.Dispose();
stream.Dispose();
gpu.Dispose();
}
// GpuPrimeWorkLimiter.Release();
limiter.Dispose();
return result;
}
@@ -194,18 +100,16 @@ public class MersenneNumberLucasLehmerGpuTester
}
}
var acceleratorIndex = AcceleratorPool.Shared.Rent();
var accelerator = _accelerators[acceleratorIndex];
var stream = accelerator.CreateStream();
var gpu = GpuContextPool.Rent();
var accelerator = gpu.Accelerator;
var kernel = GetBatchKernel(accelerator);
var expBuffer = accelerator.Allocate1D<ulong>(count);
ArrayPool<ulong> ulongPool = ThreadStaticPools.UlongPool;
ulong[] expArray = ulongPool.Rent(count);
ulong[] expArray = ArrayPool<ulong>.Shared.Rent(count);
exponents.CopyTo(expArray);
expBuffer.View.CopyFromCPU(stream, ref expArray[0], count);
expBuffer.View.CopyFromCPU(ref expArray[0], count);
ArrayPool<GpuUInt128> gpuUInt128Pool = ThreadStaticPools.GpuUInt128Pool;
GpuUInt128[] modulusArray = gpuUInt128Pool.Rent(count);
GpuUInt128[] modulusArray = ArrayPool<GpuUInt128>.Shared.Rent(count);
for (int i = 0; i < count; i++)
{
// TODO: Replace this per-exponent shift with a small shared table (one entry per supported exponent < 128)
@@ -214,20 +118,19 @@ public class MersenneNumberLucasLehmerGpuTester
}
var modBuffer = accelerator.Allocate1D<GpuUInt128>(count);
modBuffer.View.CopyFromCPU(stream, ref modulusArray[0], count);
modBuffer.View.CopyFromCPU(ref modulusArray[0], count);
var stateBuffer = accelerator.Allocate1D<GpuUInt128>(count);
var lucasLehmerBatchKernel = GetLucasLehmerBatchKernel(accelerator);
lucasLehmerBatchKernel(stream, count, expBuffer.View, modBuffer.View, stateBuffer.View);
stateBuffer.View.CopyToCPU(stream, ref residues[0], count);
stream.Synchronize();
var stateBuffer = accelerator.Allocate1D<GpuUInt128>(count);
kernel(count, expBuffer.View, modBuffer.View, stateBuffer.View);
accelerator.Synchronize();
stateBuffer.View.CopyToCPU(ref residues[0], count);
stateBuffer.Dispose();
modBuffer.Dispose();
expBuffer.Dispose();
gpuUInt128Pool.Return(modulusArray);
ulongPool.Return(expArray);
stream.Dispose();
ArrayPool<GpuUInt128>.Shared.Return(modulusArray);
ArrayPool<ulong>.Shared.Return(expArray);
gpu.Dispose();
}
public void IsMersennePrimeBatch(ReadOnlySpan<ulong> exponents, Span<bool> results)
@@ -238,27 +141,23 @@ public class MersenneNumberLucasLehmerGpuTester
throw new ArgumentException("Result span too small", nameof(results));
}
ArrayPool<GpuUInt128> gpuUInt128Pool = ThreadStaticPools.GpuUInt128Pool;
GpuUInt128[] buffer = gpuUInt128Pool.Rent(count);
GpuUInt128[] buffer = ArrayPool<GpuUInt128>.Shared.Rent(count);
ComputeResidues(exponents, buffer.AsSpan(0, count));
for (int i = 0; i < count; i++)
{
results[i] = buffer[i].IsZero;
}
gpuUInt128Pool.Return(buffer);
ArrayPool<GpuUInt128>.Shared.Return(buffer);
}
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
private bool IsMersennePrimeNtt(ulong exponent, GpuUInt128 nttMod, GpuUInt128 primitiveRoot, bool runOnGpu)
{
var acceleratorIndex = AcceleratorPool.Shared.Rent();
var accelerator = _accelerators[acceleratorIndex];
var stream = accelerator.CreateStream();
var gpu = GpuContextPool.Rent();
var accelerator = gpu.Accelerator;
var addKernel = GetAddSmallKernel(accelerator);
var subKernel = GetSubSmallKernel(accelerator);
var reduceKernel = GetReduceKernel(accelerator);
var isZeroKernel = GetIsZeroKernel(accelerator);
var reduceKernel = GetReduceKernel(accelerator);
var zeroKernel = GetIsZeroKernel(accelerator);
int limbCount = (int)((exponent + 127UL) / 128UL);
int target = limbCount * 2;
@@ -268,9 +167,8 @@ public class MersenneNumberLucasLehmerGpuTester
transformLength <<= 1;
}
var stateBuffer = accelerator.Allocate1D<GpuUInt128>(transformLength);
stateBuffer.MemSetToZero(stream);
var addSmallKernel = GetAddSmallKernel(accelerator);
addSmallKernel(stream, 1, 4UL, stateBuffer.View);
stateBuffer.MemSetToZero();
addKernel(1, 4UL, stateBuffer.View);
// TODO(LL-SLICE): Slice Lucas–Lehmer iterations into short batches to
// avoid long-running kernels and TDR. Example: process 8–64 iterations
@@ -285,26 +183,27 @@ public class MersenneNumberLucasLehmerGpuTester
for (int s = 0; s < iter; s++)
{
// Square in NTT domain with staged kernels (short runtime per kernel).
NttGpuMath.SquareDevice(accelerator, stream, stateBuffer.View, nttMod, primitiveRoot);
subKernel(stream, 1, 2UL, stateBuffer.View);
reduceKernel(stream, 1, exponent, stateBuffer.View);
NttGpuMath.SquareDevice(accelerator, stateBuffer.View, nttMod, primitiveRoot);
subKernel(1, 2UL, stateBuffer.View);
reduceKernel(1, exponent, stateBuffer.View);
}
// Synchronize between slices to yield to scheduler and avoid TDR.
accelerator.Synchronize();
i += (ulong)iter;
}
reduceKernel(stream, 1, exponent, stateBuffer.View);
var resultBuffer = accelerator.Allocate1D<byte>(1);
isZeroKernel(stream, 1, stateBuffer.View, resultBuffer.View);
Span<byte> result = stackalloc byte[1];
resultBuffer.View.CopyToCPU(stream, result);
stream.Synchronize();
reduceKernel(1, exponent, stateBuffer.View);
var resultBuffer = accelerator.Allocate1D<byte>(1);
zeroKernel(1, stateBuffer.View, resultBuffer.View);
accelerator.Synchronize();
byte[] result = new byte[1];
resultBuffer.View.CopyToCPU(result);
bool isPrime = result[0] != 0;
resultBuffer.Dispose();
stateBuffer.Dispose();
stream.Dispose();
gpu.Dispose();
return isPrime;
}
@@ -573,4 +472,6 @@ public class MersenneNumberLucasLehmerGpuTester
return result;
}
}
@@ -4,76 +4,62 @@ namespace PerfectNumbers.Core.Gpu;
public class MersenneNumberOrderGpuTester(GpuKernelType kernelType, bool useGpuOrder)
{
private readonly GpuKernelType _kernelType = kernelType;
private readonly bool _useGpuOrder = useGpuOrder;
private readonly GpuKernelType _kernelType = kernelType;
private readonly bool _useGpuOrder = useGpuOrder;
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
public void Scan(ulong exponent, UInt128 twoP, LastDigit lastDigit, UInt128 maxK, ref bool isPrime)
{
var gpuLease = GpuKernelPool.GetKernel(_useGpuOrder);
var accelerator = gpuLease.Accelerator;
var stream = gpuLease.Stream;
int batchSize = GpuConstants.ScanBatchSize; // large batch improves GPU occupancy and avoids TDR
UInt128 kStart = UInt128.One;
ulong divMul = (ulong)((((UInt128)1 << 64) - UInt128.One) / exponent) + 1UL;
byte last = lastDigit == LastDigit.Seven ? (byte)1 : (byte)0; // ILGPU kernels do not support bool parameters
public void Scan(ulong exponent, UInt128 twoP, LastDigit lastDigit, UInt128 maxK, ref bool isPrime)
{
// GpuPrimeWorkLimiter.Acquire();
// var accelerator = SharedGpuContext.Accelerator;
var acceleratorIndex = AcceleratorPool.Shared.Rent();
var accelerator = _accelerators[acceleratorIndex];
var stream = accelerator.CreateStream();
int batchSize = GpuConstants.ScanBatchSize; // large batch improves GPU occupancy and avoids TDR
UInt128 kStart = UInt128.One;
ulong divMul = (ulong)((((UInt128)1 << 64) - UInt128.One) / exponent) + 1UL;
byte last = lastDigit == LastDigit.Seven ? (byte)1 : (byte)0; // ILGPU kernels do not support bool parameters
var kernel = _kernelType switch
{
GpuKernelType.Pow2Mod => gpuLease.Pow2ModOrderKernel,
_ => gpuLease.IncrementalOrderKernel,
};
KernelContainer kernels = GpuKernelPool.GetOrAddKernels(acceleratorIndex, stream, KernelType.Pow2ModOrderKernelScan | KernelType.IncrementalOrderKernelScan);
var kernel = _kernelType switch
{
GpuKernelType.Pow2Mod => kernels.Pow2ModOrder!,
_ => kernels.IncrementalOrder!,
};
var foundBuffer = accelerator.Allocate1D<int>(1); // TODO: Replace this allocation with the pooled device buffer from GpuOrderKernelBenchmarks so repeated scans reuse the pinned staging memory instead of allocating per run.
exponent.Mod10_8_5_3Steps(out ulong step10, out ulong step8, out ulong step5, out ulong step3);
MemoryBuffer1D<int, ILGPU.Stride1D.Dense>? foundBuffer;
// lock (accelerator)
{
foundBuffer = accelerator.Allocate1D<int>(1); // TODO: Replace this allocation with the pooled device buffer from GpuOrderKernelBenchmarks so repeated scans reuse the pinned staging memory instead of allocating per run.
UInt128 remaining;
int currentSize;
int found = 0;
while (kStart <= maxK && Volatile.Read(ref isPrime))
{
remaining = maxK - kStart + 1UL;
currentSize = remaining > (UInt128)batchSize ? batchSize : (int)remaining;
// This clear is required because the result may not always be set. Remove it after the kernels are modified to always set the result.
foundBuffer.MemSetToZero();
// Precompute residue automaton bases for this batch
UInt128 q0 = twoP * kStart + 1UL;
// TODO: Replace these modulo recomputations with the divisor-cycle stepping deltas captured in
// MersenneDivisorCycleLengthGpuBenchmarks so each batch advances via cached residues from the
// single snapshot block instead of recalculating mod 10/8/5/3 in every iteration.
q0.Mod10_8_5_3(out ulong q0m10, out ulong q0m8, out ulong q0m5, out ulong q0m3);
var kernelArgs = new ResidueAutomatonArgs(q0m10, step10, q0m8, step8, q0m3, step3, q0m5, step5);
}
exponent.Mod10_8_5_3Steps(out ulong step10, out ulong step8, out ulong step5, out ulong step3);
// Ensure device has small cycles table for early rejections in order kernels
var smallCyclesView = GpuKernelPool.EnsureSmallCyclesOnDevice(accelerator);
kernel(stream, currentSize, exponent, (GpuUInt128)twoP, (GpuUInt128)kStart, last, divMul,
kernelArgs, foundBuffer.View, smallCyclesView);
UInt128 remaining;
int currentSize;
int found = 0;
stream.Synchronize();
foundBuffer.View.CopyToCPU(ref found, 1);
if (found != 0)
{
Volatile.Write(ref isPrime, false);
break;
}
var smallCyclesView = GpuKernelPool.GetSmallCyclesOnDevice(kernels);
while (kStart <= maxK && Volatile.Read(ref isPrime))
{
remaining = maxK - kStart + 1UL;
currentSize = remaining > (UInt128)batchSize ? batchSize : (int)remaining;
// This clear is required because the result may not always be set. Remove it after the kernels are modified to always set the result.
foundBuffer.MemSetToZero(stream);
// Precompute residue automaton bases for this batch
UInt128 q0 = twoP * kStart + 1UL;
// TODO: Replace these modulo recomputations with the divisor-cycle stepping deltas captured in
// MersenneDivisorCycleLengthGpuBenchmarks so each batch advances via cached residues from the
// single snapshot block instead of recalculating mod 10/8/5/3 in every iteration.
q0.Mod10_8_5_3(out ulong q0m10, out ulong q0m8, out ulong q0m5, out ulong q0m3);
var kernelArgs = new ResidueAutomatonArgs(q0m10, step10, q0m8, step8, q0m3, step3, q0m5, step5);
kStart += (UInt128)currentSize;
}
// Ensure device has small cycles table for early rejections in order kernels
kernel(
stream, currentSize, exponent, (GpuUInt128)twoP, (GpuUInt128)kStart,
last, divMul, kernelArgs, foundBuffer.View, smallCyclesView
);
foundBuffer.View.CopyToCPU(stream, ref found, 1);
stream.Synchronize();
if (found != 0)
{
Volatile.Write(ref isPrime, false);
break;
}
kStart += (UInt128)currentSize;
}
stream.Dispose();
foundBuffer.Dispose();
// GpuPrimeWorkLimiter.Release();
}
foundBuffer.Dispose();
gpuLease.Dispose();
}
}
@@ -1,4 +1,9 @@
using System;
using System.Buffers;
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.Runtime.InteropServices;
using System.Threading;
using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Runtime;
@@ -7,211 +12,185 @@ namespace PerfectNumbers.Core.Gpu;
public class MersenneNumberResidueGpuTester(bool useGpuOrder)
{
private readonly bool _useGpuOrder = useGpuOrder;
private readonly bool _useGpuOrder = useGpuOrder;
private readonly ConcurrentBag<GpuContextPool.GpuContextLease> _acceleratorPool = new();
private readonly ConcurrentDictionary<Accelerator, Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>> _pow2ModKernelCache = new(AcceleratorReferenceComparer.Instance);
private readonly ConcurrentDictionary<Accelerator, ConcurrentBag<ResidueResources>> _resourcePools = new(AcceleratorReferenceComparer.Instance);
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>>? _pow2ModKernel;
// TODO: Integrate MersenneDivisorCycles.Shared to consult cycle lengths for small q (<= 4M) and fast-reject
// candidates without launching heavy kernels. Consider a device-visible constant buffer per-accelerator
// via GpuKernelPool to avoid host round-trips.
// TODO: When cycles are missing for larger q values, compute only the single required cycle on the device
// requested by the caller, skip queuing additional block generation, and keep the snapshot cache untouched.
[ThreadStatic]
private static Queue<ResidueResources>? _resourcePools;
// GPU residue variant: check 2^p % q == 1 for q = 2*p*k + 1.
public void Scan(ulong exponent, UInt128 twoP, LastDigit lastDigit, UInt128 maxK, ref bool isPrime)
{
var limiter = GpuPrimeWorkLimiter.Acquire();
var gpuLease = RentAccelerator();
var accelerator = gpuLease.Accelerator;
// TODO: Integrate MersenneDivisorCycles.Shared to consult cycle lengths for small q (<= 4M) and fast-reject
// candidates without launching heavy kernels. Consider a device-visible constant buffer per-accelerator
// via GpuKernelPool to avoid host round-trips.
// TODO: When cycles are missing for larger q values, compute only the single required cycle on the device
// requested by the caller, skip queuing additional block generation, and keep the snapshot cache untouched.
// Monitor.Enter(gpuLease.ExecutionLock);
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
var stream = accelerator.CreateStream();
var kernel = GetPow2ModKernel(accelerator);
var resources = RentResources(accelerator, GpuConstants.ScanBatchSize);
// GPU residue variant: check 2^p % q == 1 for q = 2*p*k + 1.
public void Scan(ulong exponent, UInt128 twoP, LastDigit lastDigit, UInt128 maxK, ref bool isPrime)
{
// GpuPrimeWorkLimiter.Acquire();
var acceleratorIndex = AcceleratorPool.Shared.Rent();
var accelerator = _accelerators[acceleratorIndex];
var orderBuffer = resources.OrderBuffer;
ulong[] orderArray = resources.OrderArray;
int batchSize = resources.Capacity;
// Monitor.Enter(gpuLease.ExecutionLock);
// Ensure device has small cycles and primes tables for in-kernel lookup
var smallCyclesView = GpuKernelPool.EnsureSmallCyclesOnDevice(accelerator);
ResiduePrimeViews primeViews = GpuKernelPool.EnsureSmallPrimesOnDevice(accelerator);
var stream = accelerator.CreateStream();
var kernel = GetPow2ModKernel(accelerator);
var resources = RentResources(accelerator, GpuConstants.ScanBatchSize);
var gpuKernels = GpuKernelPool.GetOrAddKernels(acceleratorIndex, stream, KernelType.SmallCycles | KernelType.SmallPrimes);
UInt128 kStart = 1UL;
UInt128 limit = maxK + UInt128.One;
byte last = lastDigit == LastDigit.Seven ? (byte)1 : (byte)0;
twoP.Mod10_8_5_3(out ulong step10, out ulong step8, out ulong step5, out ulong step3);
step10 = step10.Mod10();
var orderBuffer = resources.OrderBuffer;
ulong[] orderArray = resources.OrderArray;
int batchSize = resources.Capacity;
GpuUInt128 twoPGpu = (GpuUInt128)twoP;
UInt128 batchSize128 = (UInt128)batchSize;
UInt128 fullBatchStep = twoP * batchSize128;
UInt128 q = twoP * kStart + UInt128.One;
// Ensure device has small cycles and primes tables for in-kernel lookup
// TODO: Pass-in the stream down the path
var smallCyclesView = GpuKernelPool.GetSmallCyclesOnDevice(gpuKernels);
ResiduePrimeViews primeViews = GpuKernelPool.GetSmallPrimesOnDevice(gpuKernels);
while (kStart < limit && Volatile.Read(ref isPrime))
{
UInt128 remaining = limit - kStart;
int currentSize = remaining > batchSize128 ? batchSize : (int)remaining;
Span<ulong> orders = orderArray.AsSpan(0, currentSize);
ref ulong ordersRef = ref MemoryMarshal.GetReference(orders);
UInt128 kStart = 1UL;
UInt128 limit = maxK + UInt128.One;
byte last = lastDigit == LastDigit.Seven ? (byte)1 : (byte)0;
twoP.Mod10_8_5_3(out ulong step10, out ulong step8, out ulong step5, out ulong step3);
step10 = step10.Mod10();
q.Mod10_8_5_3(out ulong q0m10, out ulong q0m8, out ulong q0m5, out ulong q0m3);
var kernelArgs = new ResidueAutomatonArgs(q0m10, step10, q0m8, step8, q0m3, step3, q0m5, step5);
GpuUInt128 twoPGpu = (GpuUInt128)twoP;
UInt128 batchSize128 = (UInt128)batchSize;
UInt128 fullBatchStep = twoP * batchSize128;
UInt128 q = twoP * kStart + UInt128.One;
kernel(stream, currentSize, exponent, twoPGpu, (GpuUInt128)kStart, last, 0UL,
kernelArgs, orderBuffer.View, smallCyclesView, primeViews.LastOne, primeViews.LastSeven, primeViews.LastOnePow2, primeViews.LastSevenPow2);
while (kStart < limit && Volatile.Read(ref isPrime))
{
UInt128 remaining = limit - kStart;
int currentSize = remaining > batchSize128 ? batchSize : (int)remaining;
Span<ulong> orders = orderArray.AsSpan(0, currentSize);
ref ulong ordersRef = ref MemoryMarshal.GetReference(orders);
stream.Synchronize();
orderBuffer.View.CopyToCPU(ref ordersRef, currentSize);
if (!Volatile.Read(ref isPrime))
{
break;
}
q.Mod10_8_5_3(out ulong q0m10, out ulong q0m8, out ulong q0m5, out ulong q0m3);
var kernelArgs = new ResidueAutomatonArgs(q0m10, step10, q0m8, step8, q0m3, step3, q0m5, step5);
bool compositeFound = false;
for (int i = 0; i < currentSize; i++)
{
if (orders[i] != 0UL)
{
Volatile.Write(ref isPrime, false);
compositeFound = true;
break;
}
}
kernel(stream, currentSize, exponent, twoPGpu, (GpuUInt128)kStart, last, 0UL,
kernelArgs, orderBuffer.View, smallCyclesView, primeViews.LastOne, primeViews.LastSeven, primeViews.LastOnePow2, primeViews.LastSevenPow2);
if (compositeFound)
{
break;
}
orderBuffer.View.CopyToCPU(stream, ref ordersRef, currentSize);
stream.Synchronize();
if (!Volatile.Read(ref isPrime))
UInt128 processed = (UInt128)currentSize;
kStart += processed;
if (kStart < limit)
{
if (processed == batchSize128)
{
q += fullBatchStep;
}
else
{
q += twoP * processed; // TODO: Swap this multiplication for the shared cycle stepping helper once residue cycles are mandatory so we can reuse the cached remainder ladder instead of performing UInt128 multiply operations.
}
}
}
ReturnResources(accelerator, resources);
stream.Dispose();
// Monitor.Exit(gpuLease.ExecutionLock);
ReturnAccelerator(gpuLease);
limiter.Dispose();
}
private Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>> GetPow2ModKernel(Accelerator accelerator) =>
_pow2ModKernelCache.GetOrAdd(
accelerator,
static acc =>
{
var loaded = acc.LoadAutoGroupedStreamKernel<Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>(Pow2ModKernels.Pow2ModKernelScan);
return (Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>)Delegate.CreateDelegate(
typeof(Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>),
loaded.Target,
loaded.Method);
});
private GpuContextPool.GpuContextLease RentAccelerator()
{
if (_acceleratorPool.TryTake(out var lease))
{
return lease;
}
return GpuContextPool.Rent();
}
private void ReturnAccelerator(GpuContextPool.GpuContextLease lease) => _acceleratorPool.Add(lease);
private ResidueResources RentResources(Accelerator accelerator, int capacity)
{
var bag = _resourcePools.GetOrAdd(accelerator, static _ => new ConcurrentBag<ResidueResources>());
while (bag.TryTake(out var resources))
{
if (resources.Capacity >= capacity)
{
break;
}
// The caller always overwrites the required elements. We don't need to worry about clearing the output buffer.
// resources.OrderBuffer.MemSetToZero();
return resources;
}
bool compositeFound = false;
for (int i = 0; i < currentSize; i++)
{
if (orders[i] != 0UL)
{
Volatile.Write(ref isPrime, false);
compositeFound = true;
break;
}
}
resources.Dispose();
}
if (compositeFound)
{
break;
}
var created = new ResidueResources(accelerator, capacity);
// The caller always overwrites the required elements. We don't need to worry about clearing the output buffer.
// created.OrderBuffer.MemSetToZero();
return created;
}
UInt128 processed = (UInt128)currentSize;
kStart += processed;
if (kStart < limit)
{
if (processed == batchSize128)
{
q += fullBatchStep;
}
else
{
q += twoP * processed; // TODO: Swap this multiplication for the shared cycle stepping helper once residue cycles are mandatory so we can reuse the cached remainder ladder instead of performing UInt128 multiply operations.
}
}
}
private void ReturnResources(Accelerator accelerator, ResidueResources resources) =>
_resourcePools.GetOrAdd(accelerator, static _ => new ConcurrentBag<ResidueResources>()).Add(resources);
ReturnResources(resources);
stream.Dispose();
// Monitor.Exit(gpuLease.ExecutionLock);
gpuKernels.Dispose();
// GpuPrimeWorkLimiter.Release();
}
private sealed class ResidueResources
{
internal ResidueResources(Accelerator accelerator, int capacity)
{
Capacity = Math.Max(1, capacity);
OrderBuffer = accelerator.Allocate1D<ulong>(Capacity);
OrderArray = ArrayPool<ulong>.Shared.Rent(Capacity);
}
private static Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>> GetPow2ModKernel(Accelerator accelerator)
{
internal MemoryBuffer1D<ulong, Stride1D.Dense> OrderBuffer { get; }
var pool = _pow2ModKernel ?? [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
internal ulong[] OrderArray { get; }
cached = CreatePow2ModKernel(accelerator);
pool[accelerator] = cached;
return cached;
}
internal int Capacity { get; }
private static Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>> CreatePow2ModKernel(Accelerator accelerator)
{
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>(Pow2ModKernels.Pow2ModKernelScan);
public void Dispose()
{
OrderBuffer.Dispose();
ArrayPool<ulong>.Shared.Return(OrderArray, clearArray: false);
}
}
var kernel = (Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>)Delegate.CreateDelegate(
typeof(Action<AcceleratorStream, Index1D, ulong, GpuUInt128, GpuUInt128, byte, ulong, ResidueAutomatonArgs, ArrayView<ulong>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<uint, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>),
loaded.Target,
loaded.Method);
return kernel;
}
private sealed class AcceleratorReferenceComparer : IEqualityComparer<Accelerator>
{
public static AcceleratorReferenceComparer Instance { get; } = new();
public bool Equals(Accelerator? x, Accelerator? y) => ReferenceEquals(x, y);
public int GetHashCode(Accelerator obj) => RuntimeHelpers.GetHashCode(obj);
}
private static ResidueResources RentResources(Accelerator accelerator, int capacity)
{
var resourcePools = _resourcePools ??= new();
if (resourcePools.TryDequeue(out var bag))
{
bag.EnsureCapacity(accelerator, capacity);
return bag;
}
return new ResidueResources(accelerator, capacity);
}
private static void ReturnResources(ResidueResources resources)
{
var resourcePools = _resourcePools ??= new();
resourcePools.Enqueue(resources);
}
private sealed class ResidueResources
{
internal ResidueResources(Accelerator accelerator, int capacity)
{
Capacity = Math.Max(1, capacity);
// lock (accelerator)
{
OrderBuffer = accelerator.Allocate1D<ulong>(Capacity);
}
OrderArray = ThreadStaticPools.UlongPool.Rent(Capacity);
}
internal void EnsureCapacity(Accelerator accelerator, int capacity)
{
if (OrderBuffer.Length >= capacity)
{
return;
}
OrderBuffer.Dispose();
ThreadStaticPools.UlongPool.Return(OrderArray);
// lock (accelerator)
{
OrderBuffer = accelerator.Allocate1D<ulong>(capacity);
}
OrderArray = ThreadStaticPools.UlongPool.Rent(capacity);
Capacity = capacity;
}
internal MemoryBuffer1D<ulong, Stride1D.Dense> OrderBuffer { get; private set; }
internal ulong[] OrderArray { get; private set; }
internal int Capacity { get; private set; }
public void Dispose()
{
OrderBuffer.Dispose();
ThreadStaticPools.UlongPool.Return(OrderArray, clearArray: false);
}
}
private sealed class AcceleratorReferenceComparer : IEqualityComparer<Accelerator>
{
public static AcceleratorReferenceComparer Instance { get; } = new();
public bool Equals(Accelerator? x, Accelerator? y) => ReferenceEquals(x, y);
public int GetHashCode(Accelerator obj) => RuntimeHelpers.GetHashCode(obj);
}
}
}
+239 -363
View File
@@ -1,3 +1,4 @@
using System.Buffers;
using System.Collections.Concurrent;
using ILGPU;
using ILGPU.Runtime;
@@ -26,64 +27,27 @@ public static class NttGpuMath
// Global backend setting for GPU transforms. Used by ForwardGpu/InverseGpu.
// TODO(NTT-OPT): Consider passing backend explicitly to avoid global state.
public static NttBackend GpuTransformBackend { get; set; } = NttBackend.Reference;
// Controls modular reduction strategy inside staged NTT paths.
public static ModReductionMode ReductionMode { get; set; } = ModReductionMode.Auto;
// Controls modular reduction strategy inside staged NTT paths.
public static ModReductionMode ReductionMode { get; set; } = ModReductionMode.Auto;
private static readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, GpuUInt128>> MulKernelCache = new(); // TODO: Replace this concurrent cache with the prewarmed accelerator-indexed tables from GpuModularArithmeticBenchmarks so kernel launches avoid dictionary lookups once the kernels are baked during startup.
private static readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, GpuUInt128>> StageKernelCache = new(); // TODO: Same as above – materialize staged kernels during startup so we can drop ConcurrentDictionary usage entirely per the benchmark guidance.
private static readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, GpuUInt128, GpuUInt128>> ScaleKernelCache = new(); // TODO: Promote to the static kernel table initialized alongside the GpuModularArithmeticBenchmarks fast path.
private static readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, ulong, ulong>> StageMontKernelCache = new(); // TODO: Inline the Montgomery kernels into the startup table instead of using a concurrent cache now that we no longer mutate state at runtime.
private static readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, ulong, ulong, ulong, ulong>> StageBarrett128KernelCache = new(); // TODO: Same plan – reuse the precomputed kernels measured fastest in MontgomeryMultiplyBenchmarks rather than looking them up dynamically.
private static readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, GpuUInt128, ulong, ulong, ulong, ulong>> ScaleBarrett128KernelCache = new(); // TODO: Collapse into the startup kernel array once Barrett128 constants are preloaded.
private static readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong, ulong>> SquareBarrett128KernelCache = new(); // TODO: Fold these kernels into the same startup table to avoid concurrent access overhead highlighted in GpuModularArithmeticBenchmarks.
private static readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong>> ToMont64KernelCache = new(); // TODO: Prebind and reuse the Montgomery conversions from MontgomeryMultiplyBenchmarks instead of storing them in a concurrent cache.
private static readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, ulong, ulong>> FromMont64KernelCache = new(); // TODO: As above – drop ConcurrentDictionary once startup prewarms every kernel.
private static readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, ulong, ulong>> SquareMont64KernelCache = new(); // TODO: Inline into the static kernel table established during initialization.
private static readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong>> ScaleMont64KernelCache = new(); // TODO: Move to the startup kernel table so Montgomery-scaled launches skip concurrent lookups.
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, GpuUInt128>>? _mulKernel; // TODO: Replace this concurrent cache with the prewarmed accelerator-indexed tables from GpuModularArithmeticBenchmarks so kernel launches avoid dictionary lookups once the kernels are baked during startup.
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream,Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, GpuUInt128>>? _stageKernel; // TODO: Replace this concurrent cache with the prewarmed accelerator-indexed tables from GpuModularArithmeticBenchmarks so kernel launches avoid dictionary lookups once the kernels are baked during startup.
private static readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, int, GpuUInt128, GpuUInt128>> ForwardKernelCache = new(); // TODO: Warm these forward kernels during initialization and store them in a plain array so the LucasLehmerGpuBenchmarks launch costs disappear.
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, GpuUInt128, GpuUInt128>>? _scaleKernel; // TODO: Replace this concurrent cache with the prewarmed accelerator-indexed tables from GpuModularArithmeticBenchmarks so kernel launches avoid dictionary lookups once the kernels are baked during startup.
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, ulong, ulong>>? _stageMontKernel; // TODO: Replace this concurrent cache with the prewarmed accelerator-indexed tables from GpuModularArithmeticBenchmarks so kernel launches avoid dictionary lookups once the kernels are baked during startup.
private static readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, int, GpuUInt128, GpuUInt128, GpuUInt128>> InverseKernelCache = new(); // TODO: Same as above – replace with startup-prepared tables per LucasLehmerGpuBenchmarks guidance.
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, ulong, ulong, ulong, ulong>>? _stageBarrett128Kernel; // TODO: Replace this concurrent cache with the prewarmed accelerator-indexed tables from GpuModularArithmeticBenchmarks so kernel launches avoid dictionary lookups once the kernels are baked during startup.
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong>>? _toMont64Kernel; // TODO: Replace this concurrent cache with the prewarmed accelerator-indexed tables from GpuModularArithmeticBenchmarks so kernel launches avoid dictionary lookups once the kernels are baked during startup.
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ulong, ulong>>? _fromMont64Kernel; // TODO: Replace this concurrent cache with the prewarmed accelerator-indexed tables from GpuModularArithmeticBenchmarks so kernel launches avoid dictionary lookups once the kernels are baked during startup.
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, GpuUInt128, ulong, ulong, ulong, ulong>>? _scaleBarrett128Kernel; // TODO: Replace this concurrent cache with the prewarmed accelerator-indexed tables from GpuModularArithmeticBenchmarks so kernel launches avoid dictionary lookups once the kernels are baked during startup.
[ThreadStatic]
private static readonly Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, GpuUInt128>>? _squareMont64Kernel; // TODO: Replace this concurrent cache with the prewarmed accelerator-indexed tables from GpuModularArithmeticBenchmarks so kernel launches avoid dictionary lookups once the kernels are baked during startup.
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong>>? _scaleMont64Kernel; // TODO: Replace this concurrent cache with the prewarmed accelerator-indexed tables from GpuModularArithmeticBenchmarks so kernel launches avoid dictionary lookups once the kernels are baked during startup.
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, int, GpuUInt128, GpuUInt128>>? _forwardKernel; // TODO: Replace this concurrent cache with the prewarmed accelerator-indexed tables from GpuModularArithmeticBenchmarks so kernel launches avoid dictionary lookups once the kernels are baked during startup.
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, int, GpuUInt128, GpuUInt128, GpuUInt128>>? _inverseKernel; // TODO: Replace this concurrent cache with the prewarmed accelerator-indexed tables from GpuModularArithmeticBenchmarks so kernel launches avoid dictionary lookups once the kernels are baked during startup.
[ThreadStatic]
private static Dictionary<Accelerator, Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, int>>? _bitReverseKernel; // TODO: Replace this concurrent cache with the prewarmed accelerator-indexed tables from GpuModularArithmeticBenchmarks so kernel launches avoid dictionary lookups once the kernels are baked during startup.
private static readonly ConcurrentDictionary<Accelerator, Action<Index1D, ArrayView<GpuUInt128>, int>> BitReverseKernelCache = new(); // TODO: Precompute bit-reversal kernels during boot so we can remove the concurrent lookup overhead flagged in the benchmarks.
private static Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, GpuUInt128> GetStageKernel(Accelerator accelerator)
{
var pool = _stageKernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, GpuUInt128>(NttButterflyKernels.StageKernel);
var kernel = KernelUtil.GetKernel(loaded);
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, GpuUInt128>>();
pool[accelerator] = cached;
return cached;
}
private sealed class SquareCacheEntry
private sealed class SquareCacheEntry
{
public MemoryBuffer1D<GpuUInt128, Stride1D.Dense> Buffer { get; }
public GpuUInt128 Root { get; }
@@ -108,7 +72,7 @@ public static class NttGpuMath
public ulong BarrettMuHigh { get; }
public ulong BarrettMuLow { get; }
public SquareCacheEntry(Accelerator accelerator, AcceleratorStream stream, int length, GpuUInt128 modulus, GpuUInt128 primitiveRoot)
public SquareCacheEntry(Accelerator accelerator, int length, GpuUInt128 modulus, GpuUInt128 primitiveRoot)
{
Buffer = accelerator.Allocate1D<GpuUInt128>(length);
Root = new GpuUInt128(primitiveRoot);
@@ -135,7 +99,7 @@ public static class NttGpuMath
// Precompute stage twiddle factors (forward and inverse) and upload to GPU.
Bits = (int)Math.Log2(length);
int twiddleCount = length - 1;
var pool = ThreadStaticPools.GpuUInt128Pool;
var pool = ArrayPool<GpuUInt128>.Shared;
var forward = pool.Rent(twiddleCount);
var inverse = pool.Rent(twiddleCount);
StageOffsets = new int[Bits];
@@ -172,9 +136,9 @@ public static class NttGpuMath
}
Twiddles = accelerator.Allocate1D<GpuUInt128>(twiddleCount);
Twiddles.View.CopyFromCPU(stream, ref forward[0], twiddleCount);
Twiddles.View.CopyFromCPU(ref forward[0], twiddleCount);
TwiddlesInv = accelerator.Allocate1D<GpuUInt128>(twiddleCount);
TwiddlesInv.View.CopyFromCPU(stream, ref inverse[0], twiddleCount);
TwiddlesInv.View.CopyFromCPU(ref inverse[0], twiddleCount);
// Prepare Montgomery constants for 64-bit moduli and twiddles in Montgomery domain.
if (modulus.High == 0UL && (ReductionMode == ModReductionMode.Auto || ReductionMode == ModReductionMode.Mont64))
@@ -202,9 +166,9 @@ public static class NttGpuMath
}
TwiddlesMont = accelerator.Allocate1D<GpuUInt128>(twiddleCount);
TwiddlesMont.View.CopyFromCPU(stream, ref forwardMont[0], twiddleCount);
TwiddlesMont.View.CopyFromCPU(ref forwardMont[0], twiddleCount);
TwiddlesInvMont = accelerator.Allocate1D<GpuUInt128>(twiddleCount);
TwiddlesInvMont.View.CopyFromCPU(stream, ref inverseMont[0], twiddleCount);
TwiddlesInvMont.View.CopyFromCPU(ref inverseMont[0], twiddleCount);
pool.Return(forwardMont, clearArray: true);
pool.Return(inverseMont, clearArray: true);
@@ -286,7 +250,7 @@ public static class NttGpuMath
private readonly record struct SquareCacheKey(int Length, GpuUInt128 Modulus, GpuUInt128 PrimitiveRoot);
private static readonly ConcurrentDictionary<SquareCacheKey, SquareCacheEntry> SquareCache = [];
private static readonly ConcurrentDictionary<Accelerator, ConcurrentDictionary<SquareCacheKey, SquareCacheEntry>> SquareCache = new();
// TODO(NTT-OPT): Add a TwiddleCache for stage-wise Cooley–Tukey NTT.
// Design:
@@ -294,10 +258,11 @@ public static class NttGpuMath
// - Store one GPU buffer with all stage twiddles, or per-stage slices.
// - Expose accessors to retrieve per-stage views used by butterfly kernels.
private static SquareCacheEntry GetSquareCache(Accelerator accelerator, AcceleratorStream stream, int length, GpuUInt128 modulus, GpuUInt128 primitiveRoot)
private static SquareCacheEntry GetSquareCache(Accelerator accelerator, int length, GpuUInt128 modulus, GpuUInt128 primitiveRoot)
{
var perAccel = SquareCache.GetOrAdd(accelerator, _ => new ConcurrentDictionary<SquareCacheKey, SquareCacheEntry>());
var key = new SquareCacheKey(length, modulus, primitiveRoot);
return SquareCache.GetOrAdd(key, _ => new SquareCacheEntry(accelerator, stream, length, modulus, primitiveRoot));
return perAccel.GetOrAdd(key, _ => new SquareCacheEntry(accelerator, length, modulus, primitiveRoot));
}
private static readonly ulong[] SmallPrimes = GenerateSmallPrimes(1000);
@@ -365,197 +330,105 @@ public static class NttGpuMath
{
if (accelerator is null)
{
foreach (var entry in SquareCache.Values)
foreach (var perAccel in SquareCache.Values)
{
entry.Dispose();
foreach (var entry in perAccel.Values)
{
entry.Dispose();
}
}
SquareCache.Clear();
MulKernelCache.Clear();
StageKernelCache.Clear();
ScaleKernelCache.Clear();
StageMontKernelCache.Clear();
StageBarrett128KernelCache.Clear();
ToMont64KernelCache.Clear();
FromMont64KernelCache.Clear();
SquareMont64KernelCache.Clear();
ScaleMont64KernelCache.Clear();
ForwardKernelCache.Clear();
InverseKernelCache.Clear();
// TODO(NTT-OPT): Clear TwiddleCache once introduced.
return;
}
var squareCache = SquareCache;
foreach (var entry in squareCache.Values)
{
entry.Dispose();
}
if (SquareCache.TryRemove(accelerator, out var cache))
{
foreach (var entry in cache.Values)
{
entry.Dispose();
}
}
MulKernelCache.TryRemove(accelerator, out _);
StageKernelCache.TryRemove(accelerator, out _);
ScaleKernelCache.TryRemove(accelerator, out _);
StageMontKernelCache.TryRemove(accelerator, out _);
StageBarrett128KernelCache.TryRemove(accelerator, out _);
ToMont64KernelCache.TryRemove(accelerator, out _);
FromMont64KernelCache.TryRemove(accelerator, out _);
SquareMont64KernelCache.TryRemove(accelerator, out _);
ScaleMont64KernelCache.TryRemove(accelerator, out _);
ForwardKernelCache.TryRemove(accelerator, out _);
InverseKernelCache.TryRemove(accelerator, out _);
// TODO(NTT-OPT): Remove per-accelerator twiddle buffers once added.
}
private static Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, int> GetBitReverseKernel(Accelerator accelerator)
{
var pool = _bitReverseKernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
private static Action<Index1D, ArrayView<GpuUInt128>, int> GetBitReverseKernel(Accelerator accelerator) =>
BitReverseKernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, int>(NttTransformKernels.BitReverseKernel));
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, int>(NttTransformKernels.BitReverseKernel);
var kernel = KernelUtil.GetKernel(loaded);
private static Action<Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, GpuUInt128> GetMulKernel(Accelerator accelerator) =>
MulKernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, GpuUInt128>(NttPointwiseKernels.MulKernel));
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, int>>();
pool[accelerator] = cached;
return cached;
}
private static Action<Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, GpuUInt128> GetStageKernel(Accelerator accelerator) =>
StageKernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, GpuUInt128>(NttButterflyKernels.StageKernel));
private static Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, int, GpuUInt128, GpuUInt128> GetForwardKernel(Accelerator accelerator)
{
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, int, GpuUInt128, GpuUInt128>(NttTransformKernels.ForwardKernel);
var kernel = KernelUtil.GetKernel(loaded);
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, int, GpuUInt128, GpuUInt128>>();
}
private static Action<Index1D, ArrayView<GpuUInt128>, GpuUInt128, GpuUInt128> GetScaleKernel(Accelerator accelerator) =>
ScaleKernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, GpuUInt128, GpuUInt128>(NttPointwiseKernels.ScaleKernel));
private static Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ulong, ulong> GetFromMont64Kernel(Accelerator accelerator)
{
var pool = _fromMont64Kernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
private static Action<Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, ulong, ulong> GetStageMontKernel(Accelerator accelerator) =>
StageMontKernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, ulong, ulong>(NttMontgomeryKernels.StageMontKernel));
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ulong, ulong>(NttMontgomeryKernels.FromMont64Kernel);
private static Action<Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, ulong, ulong, ulong, ulong> GetStageBarrett128Kernel(Accelerator accelerator) =>
StageBarrett128KernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, ulong, ulong, ulong, ulong>(NttBarrettKernels.StageBarrett128Kernel));
var kernel = KernelUtil.GetKernel(loaded);
private static Action<Index1D, ArrayView<GpuUInt128>, GpuUInt128, ulong, ulong, ulong, ulong> GetScaleBarrett128Kernel(Accelerator accelerator) =>
ScaleBarrett128KernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, GpuUInt128, ulong, ulong, ulong, ulong>(NttBarrettKernels.ScaleBarrett128Kernel));
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ulong, ulong>>();
pool[accelerator] = cached;
return cached;
}
private static Action<Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong, ulong> GetSquareBarrett128Kernel(Accelerator accelerator) =>
SquareBarrett128KernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong, ulong>(NttBarrettKernels.SquareBarrett128Kernel));
private static Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, int, GpuUInt128, GpuUInt128, GpuUInt128> GetInverseKernel(Accelerator accelerator)
{
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, int, GpuUInt128, GpuUInt128, GpuUInt128>(NttTransformKernels.InverseKernel);
var kernel = KernelUtil.GetKernel(loaded);
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, int, GpuUInt128, GpuUInt128, GpuUInt128>>();
}
private static Action<Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong> GetToMont64Kernel(Accelerator accelerator) =>
ToMont64KernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong>(NttMontgomeryKernels.ToMont64Kernel));
private static Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, GpuUInt128> GetMulKernel(Accelerator accelerator)
{
var pool = _mulKernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
private static Action<Index1D, ArrayView<GpuUInt128>, ulong, ulong> GetFromMont64Kernel(Accelerator accelerator) =>
FromMont64KernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ulong, ulong>(NttMontgomeryKernels.FromMont64Kernel));
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, GpuUInt128>(NttPointwiseKernels.MulKernel);
var kernel = KernelUtil.GetKernel(loaded);
private static Action<Index1D, ArrayView<GpuUInt128>, ulong, ulong> GetSquareMont64Kernel(Accelerator accelerator) =>
SquareMont64KernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ulong, ulong>(NttMontgomeryKernels.SquareMont64Kernel));
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, GpuUInt128>>();
pool[accelerator] = cached;
return cached;
}
private static Action<Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong> GetScaleMont64Kernel(Accelerator accelerator) =>
ScaleMont64KernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong>(NttMontgomeryKernels.ScaleMont64Kernel));
private static Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, GpuUInt128, GpuUInt128> GetScaleKernel(Accelerator accelerator)
{
var pool = _scaleKernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
private static Action<Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, int, GpuUInt128, GpuUInt128> GetForwardKernel(Accelerator accelerator) =>
ForwardKernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, int, GpuUInt128, GpuUInt128>(NttTransformKernels.ForwardKernel));
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, GpuUInt128, GpuUInt128>(NttPointwiseKernels.ScaleKernel);
var kernel = KernelUtil.GetKernel(loaded);
// TODO(NTT-OPT): Introduce stage-wise Cooley–Tukey kernels and a
// per-(accelerator,length,modulus,root) twiddle cache. The plan:
// - Precompute twiddle factors for all stages once and cache on GPU.
// - Replace the current O(n^2) ForwardKernel with O(n log n) butterflies.
// - Provide accessors like GetStageKernel(...) and GetTwiddleBuffer(...).
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, GpuUInt128, GpuUInt128>>();
pool[accelerator] = cached;
return cached;
}
private static Action<Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, int, GpuUInt128, GpuUInt128, GpuUInt128> GetInverseKernel(Accelerator accelerator) =>
InverseKernelCache.GetOrAdd(accelerator, acc => acc.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ArrayView<GpuUInt128>, int, GpuUInt128, GpuUInt128, GpuUInt128>(NttTransformKernels.InverseKernel));
private static Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, GpuUInt128, ulong, ulong, ulong, ulong> GetScaleBarrett128Kernel(Accelerator accelerator)
{
var pool = _scaleBarrett128Kernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
// TODO(NTT-OPT): Mirror the forward stage-wise design for the inverse
// transform. Precompute inverse twiddles and a normalization factor
// (n^-1 mod m). Launch one short kernel per stage to avoid TDR.
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, GpuUInt128, ulong, ulong, ulong, ulong>(NttBarrettKernels.ScaleBarrett128Kernel);
var kernel = KernelUtil.GetKernel(loaded);
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, GpuUInt128, ulong, ulong, ulong, ulong>>();
pool[accelerator] = cached;
return cached;
}
private static Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong> GetScaleMont64Kernel(Accelerator accelerator)
{
var pool = _scaleMont64Kernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong>(NttMontgomeryKernels.ScaleMont64Kernel);
var kernel = KernelUtil.GetKernel(loaded);
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong>>();
pool[accelerator] = cached;
return cached;
}
private static Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, ulong, ulong, ulong, ulong> GetStageBarrett128Kernel(Accelerator accelerator)
{
var pool = _stageBarrett128Kernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, ulong, ulong, ulong, ulong>(NttBarrettKernels.StageBarrett128Kernel);
var kernel = KernelUtil.GetKernel(loaded);
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, ulong, ulong, ulong, ulong>>();
pool[accelerator] = cached;
return cached;
}
private static Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, ulong, ulong> GetStageMontKernel(Accelerator accelerator)
{
var pool = _stageMontKernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, ulong, ulong>(NttMontgomeryKernels.StageMontKernel);
var kernel = KernelUtil.GetKernel(loaded);
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, int, int, int, ArrayView<GpuUInt128>, ulong, ulong>>();
pool[accelerator] = cached;
return cached;
}
private static Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong> GetToMont64Kernel(Accelerator accelerator)
{
var pool = _toMont64Kernel ??= [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
var loaded = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong>(NttMontgomeryKernels.ToMont64Kernel);
var kernel = KernelUtil.GetKernel(loaded);
cached = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView<GpuUInt128>, ulong, ulong, ulong>>();
pool[accelerator] = cached;
return cached;
}
// TODO(NTT-OPT): Mirror the forward stage-wise design for the inverse
// transform. Precompute inverse twiddles and a normalization factor
// (n^-1 mod m). Launch one short kernel per stage to avoid TDR.
public static void BitReverse(Span<GpuUInt128> values)
public static void BitReverse(Span<GpuUInt128> values)
{
int n = values.Length;
int bits = (int)Math.Log2(n);
@@ -573,22 +446,21 @@ public static class NttGpuMath
{
int n = values.Length;
int bits = (int)Math.Log2(n);
var acceleratorIndex = AcceleratorPool.Shared.Rent();
var accelerator = _accelerators[acceleratorIndex];
var pool = ThreadStaticPools.GpuUInt128Pool;
var gpu = GpuContextPool.Rent();
var accelerator = gpu.Accelerator;
var kernel = GetBitReverseKernel(accelerator);
var pool = ArrayPool<GpuUInt128>.Shared;
var array = pool.Rent(n);
values.CopyTo(array);
var buffer = accelerator.Allocate1D<GpuUInt128>(n);
var stream = accelerator.CreateStream();
buffer.View.CopyFromCPU(stream, ref array[0], n);
var bitReverseKernel = GetBitReverseKernel(accelerator);
bitReverseKernel(stream, n, buffer.View, bits);
buffer.View.CopyToCPU(stream, ref array[0], n);
stream.Synchronize();
buffer.View.CopyFromCPU(ref array[0], n);
kernel(n, buffer.View, bits);
accelerator.Synchronize();
buffer.View.CopyToCPU(ref array[0], n);
array.AsSpan(0, n).CopyTo(values);
pool.Return(array, clearArray: true);
buffer.Dispose();
stream.Dispose();
gpu.Dispose();
}
@@ -636,30 +508,30 @@ public static class NttGpuMath
private static void ForwardGpuReference(Span<GpuUInt128> values, GpuUInt128 modulus, GpuUInt128 primitiveRoot)
{
int n = (int)values.Length;
var acceleratorIndex = AcceleratorPool.Shared.Rent();
var accelerator = _accelerators[acceleratorIndex];
var stream = accelerator.CreateStream();
var pool = ThreadStaticPools.GpuUInt128Pool;
var gpu = GpuContextPool.Rent();
var accelerator = gpu.Accelerator;
var kernel = GetForwardKernel(accelerator);
var pool = ArrayPool<GpuUInt128>.Shared;
var inputArray = pool.Rent(n);
var outputArray = pool.Rent(n);
values.CopyTo(inputArray);
var inputBuffer = accelerator.Allocate1D<GpuUInt128>(n);
var outputBuffer = accelerator.Allocate1D<GpuUInt128>(n);
inputBuffer.View.CopyFromCPU(stream, ref inputArray[0], n);
inputBuffer.View.CopyFromCPU(ref inputArray[0], n);
UInt128 modValue = modulus;
UInt128 expBase = (modValue - 1UL) / (ulong)n;
var root = new GpuUInt128(primitiveRoot);
root.ModPow((ulong)expBase, modulus);
var forwardKernel = GetForwardKernel(accelerator);
forwardKernel(stream, n, inputBuffer.View, outputBuffer.View, n, modulus, root);
outputBuffer.View.CopyToCPU(stream, ref outputArray[0], n);
stream.Synchronize();
root.ModPow((ulong)expBase, modulus);
kernel(n, inputBuffer.View, outputBuffer.View, n, modulus, root);
accelerator.Synchronize();
outputBuffer.View.CopyToCPU(ref outputArray[0], n);
outputArray.AsSpan(0, n).CopyTo(values);
pool.Return(inputArray, clearArray: true);
pool.Return(outputArray, clearArray: true);
outputBuffer.Dispose();
inputBuffer.Dispose();
stream.Dispose();
gpu.Dispose();
}
public static void Inverse(Span<GpuUInt128> values, GpuUInt128 modulus, GpuUInt128 primitiveRoot)
@@ -733,16 +605,16 @@ public static class NttGpuMath
private static void InverseGpuReference(Span<GpuUInt128> values, GpuUInt128 modulus, GpuUInt128 primitiveRoot)
{
int n = values.Length;
var acceleratorIndex = AcceleratorPool.Shared.Rent();
var accelerator = _accelerators[acceleratorIndex];
var stream = accelerator.CreateStream();
var pool = ThreadStaticPools.GpuUInt128Pool;
var gpu = GpuContextPool.Rent();
var accelerator = gpu.Accelerator;
var kernel = GetInverseKernel(accelerator);
var pool = ArrayPool<GpuUInt128>.Shared;
var inputArray = pool.Rent(n);
var outputArray = pool.Rent(n);
values.CopyTo(inputArray);
var inputBuffer = accelerator.Allocate1D<GpuUInt128>(n);
var outputBuffer = accelerator.Allocate1D<GpuUInt128>(n);
inputBuffer.View.CopyFromCPU(stream, ref inputArray[0], n);
inputBuffer.View.CopyFromCPU(ref inputArray[0], n);
UInt128 modValue = modulus;
UInt128 expBase = (modValue - 1UL) / (ulong)n;
var root = new GpuUInt128(primitiveRoot);
@@ -758,78 +630,78 @@ public static class NttGpuMath
}
var nInv = new GpuUInt128((UInt128)n);
if (modulus.High == 0UL)
{
nInv.ModInv(modulus.Low);
}
else
{
nInv.ModInv(modulus);
}
var inverseKernel = GetInverseKernel(accelerator);
inverseKernel(stream, n, inputBuffer.View, outputBuffer.View, n, modulus, rootInv, nInv);
outputBuffer.View.CopyToCPU(stream, ref outputArray[0], n);
stream.Synchronize();
if (modulus.High == 0UL)
{
nInv.ModInv(modulus.Low);
}
else
{
nInv.ModInv(modulus);
}
kernel(n, inputBuffer.View, outputBuffer.View, n, modulus, rootInv, nInv);
accelerator.Synchronize();
outputBuffer.View.CopyToCPU(ref outputArray[0], n);
outputArray.AsSpan(0, n).CopyTo(values);
pool.Return(inputArray, clearArray: true);
pool.Return(outputArray, clearArray: true);
outputBuffer.Dispose();
inputBuffer.Dispose();
stream.Dispose();
gpu.Dispose();
}
private static void ForwardGpuStaged(Span<GpuUInt128> values, GpuUInt128 modulus, GpuUInt128 primitiveRoot)
{
int n = values.Length;
var acceleratorIndex = AcceleratorPool.Shared.Rent();
var accelerator = _accelerators[acceleratorIndex];
var stream = accelerator.CreateStream();
var gpu = GpuContextPool.Rent();
var accelerator = gpu.Accelerator;
var buffer = accelerator.Allocate1D<GpuUInt128>(n);
buffer.View.CopyFromCPU(stream, ref values[0], n);
var cache = GetSquareCache(accelerator, stream, n, modulus, primitiveRoot);
ForwardDevice(accelerator, stream, buffer.View, n, modulus, cache);
buffer.View.CopyToCPU(stream, ref values[0], n);
stream.Synchronize();
stream.Dispose();
buffer.View.CopyFromCPU(ref values[0], n);
var cache = GetSquareCache(accelerator, n, modulus, primitiveRoot);
ForwardDevice(accelerator, buffer.View, n, modulus, cache);
buffer.View.CopyToCPU(ref values[0], n);
buffer.Dispose();
gpu.Dispose();
}
private static void InverseGpuStaged(Span<GpuUInt128> values, GpuUInt128 modulus, GpuUInt128 primitiveRoot)
{
int n = values.Length;
var acceleratorIndex = AcceleratorPool.Shared.Rent();
var accelerator = _accelerators[acceleratorIndex];
var stream = accelerator.CreateStream();
var gpu = GpuContextPool.Rent();
var accelerator = gpu.Accelerator;
var buffer = accelerator.Allocate1D<GpuUInt128>(n);
buffer.View.CopyFromCPU(stream, ref values[0], n);
var cache = GetSquareCache(accelerator, stream, n, modulus, primitiveRoot);
InverseDevice(accelerator, stream, buffer.View, n, modulus, cache);
buffer.View.CopyToCPU(stream, ref values[0], n);
stream.Synchronize();
stream.Dispose();
buffer.View.CopyFromCPU(ref values[0], n);
var cache = GetSquareCache(accelerator, n, modulus, primitiveRoot);
InverseDevice(accelerator, buffer.View, n, modulus, cache);
buffer.View.CopyToCPU(ref values[0], n);
buffer.Dispose();
gpu.Dispose();
}
private static void ForwardDevice(Accelerator accelerator, AcceleratorStream stream, ArrayView<GpuUInt128> data, int length, GpuUInt128 modulus, SquareCacheEntry cache)
{
var bitReverseKernel = GetBitReverseKernel(accelerator);
bitReverseKernel(stream, length, data, cache.Bits);
private static void ForwardDevice(Accelerator accelerator, ArrayView<GpuUInt128> data, int length, GpuUInt128 modulus, SquareCacheEntry cache)
{
var bitKernel = GetBitReverseKernel(accelerator);
bitKernel(length, data, cache.Bits);
accelerator.Synchronize();
if (cache.UseMontgomery64)
{
var toMont64Kernel = GetToMont64Kernel(accelerator);
toMont64Kernel(stream, length, data, cache.ModulusLow, cache.MontNPrime64, cache.MontR2Mod64);
{
var toMont = GetToMont64Kernel(accelerator);
toMont(length, data, cache.ModulusLow, cache.MontNPrime64, cache.MontR2Mod64);
accelerator.Synchronize();
var stageKernel = GetStageMontKernel(accelerator);
int butterflies = length >> 1;
for (int s = 0; s < cache.Bits; s++)
{
int len = 1 << (s + 1);
int half = len >> 1;
stageKernel(stream, butterflies, data, len, half, cache.StageOffsets[s], cache.TwiddlesMont!.View, cache.ModulusLow, cache.MontNPrime64);
}
var fromMont64Kernel = GetFromMont64Kernel(accelerator);
fromMont64Kernel(stream, length, data, cache.ModulusLow, cache.MontNPrime64);
int butterflies = length >> 1;
for (int s = 0; s < cache.Bits; s++)
{
int len = 1 << (s + 1);
int half = len >> 1;
stageKernel(butterflies, data, len, half, cache.StageOffsets[s], cache.TwiddlesMont!.View, cache.ModulusLow, cache.MontNPrime64);
accelerator.Synchronize();
}
var fromMont = GetFromMont64Kernel(accelerator);
fromMont(length, data, cache.ModulusLow, cache.MontNPrime64);
}
else if (cache.UseBarrett128)
{
@@ -839,7 +711,8 @@ public static class NttGpuMath
{
int len = 1 << (s + 1);
int half = len >> 1;
stageKernel(stream, butterflies, data, len, half, cache.StageOffsets[s], cache.Twiddles.View, cache.ModulusHigh, cache.ModulusLow, cache.BarrettMuHigh, cache.BarrettMuLow);
stageKernel(butterflies, data, len, half, cache.StageOffsets[s], cache.Twiddles.View, cache.ModulusHigh, cache.ModulusLow, cache.BarrettMuHigh, cache.BarrettMuLow);
accelerator.Synchronize();
}
}
else
@@ -850,67 +723,72 @@ public static class NttGpuMath
{
int len = 1 << (s + 1);
int half = len >> 1;
stageKernel(stream, butterflies, data, len, half, cache.StageOffsets[s], cache.Twiddles.View, modulus);
stageKernel(butterflies, data, len, half, cache.StageOffsets[s], cache.Twiddles.View, modulus);
accelerator.Synchronize();
}
}
stream.Synchronize();
accelerator.Synchronize();
}
private static void InverseDevice(Accelerator accelerator, AcceleratorStream stream, ArrayView<GpuUInt128> data, int length, GpuUInt128 modulus, SquareCacheEntry cache)
{
var bitReverseKernel = GetBitReverseKernel(accelerator);
bitReverseKernel(stream, length, data, cache.Bits);
private static void InverseDevice(Accelerator accelerator, ArrayView<GpuUInt128> data, int length, GpuUInt128 modulus, SquareCacheEntry cache)
{
var bitKernel = GetBitReverseKernel(accelerator);
bitKernel(length, data, cache.Bits);
accelerator.Synchronize();
if (cache.UseMontgomery64)
{
var toMont64Kernel = GetToMont64Kernel(accelerator);
toMont64Kernel(stream, length, data, cache.ModulusLow, cache.MontNPrime64, cache.MontR2Mod64);
{
var toMont = GetToMont64Kernel(accelerator);
toMont(length, data, cache.ModulusLow, cache.MontNPrime64, cache.MontR2Mod64);
accelerator.Synchronize();
var stageKernel = GetStageMontKernel(accelerator);
int butterflies = length >> 1;
for (int s = 0; s < cache.Bits; s++)
{
int len = 1 << (s + 1);
int half = len >> 1;
stageKernel(stream, butterflies, data, len, half, cache.StageOffsets[s], cache.TwiddlesInvMont!.View, cache.ModulusLow, cache.MontNPrime64);
}
var scaleMont64Kernel = GetScaleMont64Kernel(accelerator);
scaleMont64Kernel(stream, length, data, cache.ModulusLow, cache.MontNPrime64, cache.MontNInvR64);
var fromMont64Kernel = GetFromMont64Kernel(accelerator);
fromMont64Kernel(stream, length, data, cache.ModulusLow, cache.MontNPrime64);
for (int s = 0; s < cache.Bits; s++)
{
int len = 1 << (s + 1);
int half = len >> 1;
stageKernel(butterflies, data, len, half, cache.StageOffsets[s], cache.TwiddlesInvMont!.View, cache.ModulusLow, cache.MontNPrime64);
accelerator.Synchronize();
}
var scaleKernel = GetScaleMont64Kernel(accelerator);
scaleKernel(length, data, cache.ModulusLow, cache.MontNPrime64, cache.MontNInvR64);
accelerator.Synchronize();
var fromMont = GetFromMont64Kernel(accelerator);
fromMont(length, data, cache.ModulusLow, cache.MontNPrime64);
}
else if (cache.UseBarrett128)
{
var stageKernel = GetStageBarrett128Kernel(accelerator);
int butterflies = length >> 1;
for (int s = 0; s < cache.Bits; s++)
{
int len = 1 << (s + 1);
int half = len >> 1;
stageKernel(stream, butterflies, data, len, half, cache.StageOffsets[s], cache.TwiddlesInv.View, cache.ModulusHigh, cache.ModulusLow, cache.BarrettMuHigh, cache.BarrettMuLow);
}
var scaleBarrett128Kernel = GetScaleBarrett128Kernel(accelerator);
scaleBarrett128Kernel(stream, length, data, cache.NInv, cache.ModulusHigh, cache.ModulusLow, cache.BarrettMuHigh, cache.BarrettMuLow);
for (int s = 0; s < cache.Bits; s++)
{
int len = 1 << (s + 1);
int half = len >> 1;
stageKernel(butterflies, data, len, half, cache.StageOffsets[s], cache.TwiddlesInv.View, cache.ModulusHigh, cache.ModulusLow, cache.BarrettMuHigh, cache.BarrettMuLow);
accelerator.Synchronize();
}
var scaleKernel = GetScaleBarrett128Kernel(accelerator);
scaleKernel(length, data, cache.NInv, cache.ModulusHigh, cache.ModulusLow, cache.BarrettMuHigh, cache.BarrettMuLow);
accelerator.Synchronize();
}
else
{
var stageKernel = GetStageKernel(accelerator);
int butterflies = length >> 1;
for (int s = 0; s < cache.Bits; s++)
{
int len = 1 << (s + 1);
int half = len >> 1;
stageKernel(stream, butterflies, data, len, half, cache.StageOffsets[s], cache.TwiddlesInv.View, modulus);
}
var scaleKernel = GetScaleKernel(accelerator);
scaleKernel(stream, length, data, cache.NInv, modulus);
for (int s = 0; s < cache.Bits; s++)
{
int len = 1 << (s + 1);
int half = len >> 1;
stageKernel(butterflies, data, len, half, cache.StageOffsets[s], cache.TwiddlesInv.View, modulus);
accelerator.Synchronize();
}
var scaleKernel = GetScaleKernel(accelerator);
scaleKernel(length, data, cache.NInv, modulus);
accelerator.Synchronize();
}
stream.Synchronize();
accelerator.Synchronize();
}
public static void Convolve(Span<GpuUInt128> left, Span<GpuUInt128> right, GpuUInt128 modulus, GpuUInt128 primitiveRoot)
@@ -922,7 +800,7 @@ public static class NttGpuMath
n <<= 1;
}
var pool = ThreadStaticPools.GpuUInt128Pool;
var pool = ArrayPool<GpuUInt128>.Shared;
var aBuffer = pool.Rent(n);
var bBuffer = pool.Rent(n);
var a = aBuffer.AsSpan(0, n);
@@ -959,7 +837,7 @@ public static class NttGpuMath
n <<= 1;
}
var pool = ThreadStaticPools.GpuUInt128Pool;
var pool = ArrayPool<GpuUInt128>.Shared;
var aBuffer = pool.Rent(n);
var bBuffer = pool.Rent(n);
var a = aBuffer.AsSpan(0, n);
@@ -993,43 +871,41 @@ public static class NttGpuMath
public static void SquareGpu(Span<GpuUInt128> values, GpuUInt128 modulus, GpuUInt128 primitiveRoot) =>
ConvolveGpu(values, values, modulus, primitiveRoot);
public static void SquareDevice(Accelerator accelerator, AcceleratorStream stream, ArrayView<GpuUInt128> values, GpuUInt128 modulus, GpuUInt128 primitiveRoot)
public static void SquareDevice(Accelerator accelerator, ArrayView<GpuUInt128> values, GpuUInt128 modulus, GpuUInt128 primitiveRoot)
{
var cache = GetSquareCache(accelerator, stream, (int)values.Length, modulus, primitiveRoot);
ForwardDevice(accelerator, stream, values, (int)values.Length, modulus, cache);
var mulKernel = GetMulKernel(accelerator);
mulKernel(stream, (int)values.Length, values, values, modulus);
InverseDevice(accelerator, stream, values, (int)values.Length, modulus, cache);
var cache = GetSquareCache(accelerator, (int)values.Length, modulus, primitiveRoot);
ForwardDevice(accelerator, values, (int)values.Length, modulus, cache);
var mul = GetMulKernel(accelerator);
mul((int)values.Length, values, values, modulus);
InverseDevice(accelerator, values, (int)values.Length, modulus, cache);
}
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
public static void PointwiseMultiply(Span<GpuUInt128> left, Span<GpuUInt128> right, GpuUInt128 modulus)
{
var acceleratorIndex = AcceleratorPool.Shared.Rent();
var accelerator = _accelerators[acceleratorIndex];
var stream = accelerator.CreateStream();
var pool = ThreadStaticPools.GpuUInt128Pool;
var gpu = GpuContextPool.Rent();
var accelerator = gpu.Accelerator;
var kernel = GetMulKernel(accelerator);
var pool = ArrayPool<GpuUInt128>.Shared;
var leftArray = pool.Rent(left.Length);
var rightArray = pool.Rent(right.Length);
left.CopyTo(leftArray);
right.CopyTo(rightArray);
var leftBuffer = accelerator.Allocate1D<GpuUInt128>(left.Length);
var rightBuffer = accelerator.Allocate1D<GpuUInt128>(right.Length);
leftBuffer.View.CopyFromCPU(stream, ref leftArray[0], left.Length);
rightBuffer.View.CopyFromCPU(stream, ref rightArray[0], right.Length);
var mulKernel = GetMulKernel(accelerator);
mulKernel(stream, left.Length, leftBuffer.View, rightBuffer.View, modulus);
leftBuffer.View.CopyToCPU(stream, ref leftArray[0], left.Length);
rightBuffer.View.CopyToCPU(stream, ref rightArray[0], right.Length);
stream.Synchronize();
leftBuffer.View.CopyFromCPU(ref leftArray[0], left.Length);
rightBuffer.View.CopyFromCPU(ref rightArray[0], right.Length);
kernel(left.Length, leftBuffer.View, rightBuffer.View, modulus);
accelerator.Synchronize();
leftBuffer.View.CopyToCPU(ref leftArray[0], left.Length);
rightBuffer.View.CopyToCPU(ref rightArray[0], right.Length);
leftArray.AsSpan(0, left.Length).CopyTo(left);
rightArray.AsSpan(0, right.Length).CopyTo(right);
pool.Return(leftArray, clearArray: true);
pool.Return(rightArray, clearArray: true);
rightBuffer.Dispose();
leftBuffer.Dispose();
stream.Dispose();
gpu.Dispose();
}
private static ulong[] GenerateSmallPrimes(int limit)
@@ -1,94 +0,0 @@
using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Runtime;
using PerfectNumbers.Core.Gpu.Accelerators;
namespace PerfectNumbers.Core.Gpu;
public static class Pow2MontgomeryGpuCalculator
{
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static ulong CalculateKeep(ulong exponent, in MontgomeryDivisorData divisor)
{
// GpuPrimeWorkLimiter.Acquire();
ulong result = 0UL;
var gpu = PrimeOrderCalculatorAccelerator.Rent(1);
int acceleratorIndex = gpu.AcceleratorIndex;
Accelerator? accelerator = gpu.Accelerator;
MemoryBuffer1D<ulong, Stride1D.Dense> exponentBuffer = gpu.Input;
MemoryBuffer1D<ulong, Stride1D.Dense> resultBuffer = gpu.OutputUlong;
AcceleratorStream stream = AcceleratorStreamPool.Rent(acceleratorIndex);
exponentBuffer.View.CopyFromCPU(stream, ref exponent, 1);
// We don't need to worry about any left-overs here.
// resultBuffer.MemSetToZero(stream);
var kernelLauncher = gpu.KeepMontgomeryKernelLauncher;
kernelLauncher(stream, 1, exponentBuffer.View, divisor, resultBuffer.View);
resultBuffer.View.CopyToCPU(stream, ref result, 1);
stream.Synchronize();
AcceleratorStreamPool.Return(acceleratorIndex, stream);
// GpuPrimeWorkLimiter.Release();
PrimeOrderCalculatorAccelerator.Return(gpu);
return result;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static ulong CalculateConvert(ulong exponent, in MontgomeryDivisorData divisor)
{
// GpuPrimeWorkLimiter.Acquire();
ulong result = 0UL;
var gpu = PrimeOrderCalculatorAccelerator.Rent(1);
MemoryBuffer1D<ulong, Stride1D.Dense> exponentBuffer = gpu.Input;
MemoryBuffer1D<ulong, Stride1D.Dense> resultBuffer = gpu.OutputUlong;
int acceleratorIndex = gpu.AcceleratorIndex;
AcceleratorStream stream = AcceleratorStreamPool.Rent(acceleratorIndex);
exponentBuffer.View.CopyFromCPU(stream, ref exponent, 1);
// We don't need to worry about any left-overs here.
// resultBuffer.MemSetToZero(stream);
var kernelLauncher = gpu.ConvertToStandardKernelLauncher!;
kernelLauncher(stream, 1, exponentBuffer.View, divisor, resultBuffer.View);
resultBuffer.View.CopyToCPU(stream, ref result, 1);
stream.Synchronize();
AcceleratorStreamPool.Return(acceleratorIndex, stream);
// GpuPrimeWorkLimiter.Release();
PrimeOrderCalculatorAccelerator.Return(gpu);
return result;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static ulong CalculateConvert(PrimeOrderCalculatorAccelerator gpu, ulong exponent, in MontgomeryDivisorData divisor)
{
ulong result = 0UL;
MemoryBuffer1D<ulong, Stride1D.Dense> exponentBuffer = gpu.Input;
MemoryBuffer1D<ulong, Stride1D.Dense> resultBuffer = gpu.OutputUlong;
int acceleratorIndex = gpu.AcceleratorIndex;
AcceleratorStream stream = AcceleratorStreamPool.Rent(acceleratorIndex);
exponentBuffer.View.CopyFromCPU(stream, ref exponent, 1);
// We don't need to worry about any left-overs here.
// resultBuffer.MemSetToZero(stream);
var accelerator = gpu.Accelerator;
var kernelLauncher = gpu.ConvertToStandardKernelLauncher;
kernelLauncher(stream, 1, exponentBuffer.View, divisor, resultBuffer.View);
resultBuffer.View.CopyToCPU(stream, ref result, 1);
stream.Synchronize();
AcceleratorStreamPool.Return(acceleratorIndex, stream);
return result;
}
}
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@@ -1,15 +0,0 @@
namespace PerfectNumbers.Core.Gpu;
public readonly struct ResidueAutomatonArgs(
ulong q0m10, ulong step10, ulong q0m8, ulong step8, ulong q0m3, ulong step3, ulong q0m5, ulong step5
)
{
public readonly ulong Q0M10 = q0m10;
public readonly ulong Step10 = step10;
public readonly ulong Q0M8 = q0m8;
public readonly ulong Step8 = step8;
public readonly ulong Q0M3 = q0m3;
public readonly ulong Step3 = step3;
public readonly ulong Q0M5 = q0m5;
public readonly ulong Step5 = step5;
}
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