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+1 -3
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@@ -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;
@@ -2,7 +2,6 @@ using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Jobs;
using Open.Numeric.Primes;
using PerfectNumbers.Core;
using PerfectNumbers.Core.Gpu.Accelerators;
namespace EvenPerfectBitScanner.Benchmarks;
@@ -26,14 +25,12 @@ public class PrimeTesterBenchmarks
return;
}
PrimeOrderCalculatorAccelerator.WarmUp();
// HeuristicGroupABPrimeTesterAccelerator.WarmUp();
_ = _heuristicTester.IsPrimeCpu(_candidates[0]);
_ = _heuristicTester.IsPrimeGpu(_candidates[0]);
_ = Prime.Numbers.IsPrime(_candidates[0]);
}
// [Benchmark]
[Benchmark]
public int HeuristicCpu()
{
HeuristicPrimeTester tester = _heuristicTester;
@@ -137,7 +134,7 @@ public class PrimeTesterBenchmarks
return primeCount;
}
// [Benchmark]
[Benchmark]
public int OpenNumericPrimes()
{
ulong[] values = _candidates;
@@ -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;
@@ -1,6 +1,8 @@
using System.Buffers.Text;
using System.IO;
using System.Runtime.CompilerServices;
using System.Text;
using System.Threading;
using PerfectNumbers.Core;
namespace EvenPerfectBitScanner;
@@ -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;
+3 -5
View File
@@ -58,14 +58,12 @@ 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(gpuPrimeThreads);
Console.WriteLine("Starting up threads...");
_ = UnboundedTaskScheduler.Instance;
int blockSize = Math.Max(1, _cliArguments.BlockSize);
@@ -628,7 +626,7 @@ internal static class Program
{
if (!(_runPrimesOnCpu
? PrimeTester.IsPrime(p)
: HeuristicCombinedPrimeTester.IsPrimeGpu(p)))
: PrimeTester.IsPrimeGpu(p)))
{
_lastCompositeP = true;
return false;
+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();
}
}
}
+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)
{
PrimeTester.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)
{
PrimeTester.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;
@@ -83,7 +83,7 @@ public class MersenneNumberDivisorByDivisorTesterTests
throw new NotSupportedException();
}
public void Return()
public void Dispose()
{
}
}
@@ -47,7 +47,7 @@ public class MersenneNumberDivisorCpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
@@ -72,7 +72,7 @@ public class MersenneNumberDivisorCpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
@@ -97,7 +97,7 @@ public class MersenneNumberDivisorCpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
}
@@ -161,7 +161,7 @@ public class MersenneNumberDivisorGpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
@@ -189,7 +189,7 @@ public class MersenneNumberDivisorGpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
@@ -217,7 +217,7 @@ public class MersenneNumberDivisorGpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
@@ -246,7 +246,7 @@ public class MersenneNumberDivisorGpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
@@ -275,7 +275,7 @@ public class MersenneNumberDivisorGpuTesterTests
}
finally
{
session.Return();
session.Dispose();
}
}
@@ -317,6 +317,7 @@ public class MersenneNumberDivisorGpuTesterTests
tableField.SetValue(cycles, originalTable);
smallCyclesField.SetValue(cycles, originalSmall);
DivisorCycleCache.Shared.RefreshSnapshot();
GpuContextPool.DisposeAll();
}
}
@@ -344,7 +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;
@@ -62,7 +62,7 @@ internal sealed class MersenneCpuDivisorScanSession : IMersenneNumberDivisorByDi
}
}
public void Return()
public void Dispose()
{
ThreadStaticPools.ReturnMersenneCpuDivisorSession(this);
}
@@ -1,495 +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)
{
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)
{
// 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.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);
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.
processedAll = true;
PrimeOrderCalculatorAccelerator.Return(gpu);
return true;
}
if (divisorCycle == 0UL)
{
Console.WriteLine($"Divisor cycle was not calculated for {prime}");
}
}
divisor.Add(step);
remainder10 = AddMod10(remainder10, step10);
remainder8 = AddMod8(remainder8, step8);
remainder3 = AddMod3(remainder3, step3);
remainder7 = AddMod7(remainder7, step7);
remainder11 = AddMod11(remainder11, step11);
}
PrimeOrderCalculatorAccelerator.Return(gpu);
processedAll = true;
return false;
}
private static bool CheckDivisors64(
ulong prime,
ulong step,
ulong limit,
ulong divisor,
ushort decimalMask,
byte step10,
byte step8,
byte step3,
byte step7,
byte step11,
byte remainder10,
byte remainder8,
byte remainder3,
byte remainder7,
byte remainder11,
out bool processedAll)
{
processedAll = false;
bool canAdvance = step <= limit;
var gpu = PrimeOrderCalculatorAccelerator.Rent(1);
if (!canAdvance)
{
if (divisor <= limit)
{
if (remainder3 != 0 && remainder7 != 0 && remainder11 != 0 && (remainder8 == 1 || remainder8 == 7) && ((decimalMask >> remainder10) & 1) != 0)
{
MontgomeryDivisorData divisorData = MontgomeryDivisorData.FromModulus(divisor);
ulong divisorCycle;
if (!MersenneDivisorCycles.TryCalculateCycleLengthForExponentCpu(
gpu,
divisor,
prime,
divisorData,
out ulong computedCycle,
out bool primeOrderFailed) || computedCycle == 0UL)
{
divisorCycle = MersenneDivisorCycles.CalculateCycleLength(
divisor,
divisorData,
skipPrimeOrderHeuristic: primeOrderFailed);
}
else
{
divisorCycle = computedCycle;
}
if (divisorCycle == prime)
{
processedAll = true;
PrimeOrderCalculatorAccelerator.Return(gpu);
return true;
}
if (divisorCycle == 0UL)
{
Console.WriteLine($"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(
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)
{
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;
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();
}
}
@@ -1,308 +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 Kernel CheckFactorsKernel;
public readonly Kernel ConvertToStandardKernel;
public readonly Action<AcceleratorStream, Index1D, ArrayView1D<ulong, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>> ConvertToStandardKernelLauncher;
public readonly Kernel HeuristicCombinedTrialDivisionKernel;
public readonly Action<AcceleratorStream, Index1D, byte, ArrayView<int>, ulong, ulong, HeuristicCombinedGpuViews> HeuristicCombinedTrialDivisionKernelLauncher;
public readonly Kernel KeepMontgomeryKernel;
public readonly Kernel PollardRhoKernel;
public readonly Kernel Pow2ModWideKernel;
public readonly Kernel SharesFactorKernel;
public readonly Kernel SmallPrimeFactorKernel;
public readonly Kernel SmallPrimeSieveKernel;
public readonly Kernel SpecialMaxKernel;
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;
}
CheckFactorsKernel = KernelUtil.GetKernel(accelerator.LoadStreamKernel<int, ulong, ArrayView1D<KeyValuePair<ulong, int>, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>>(PrimeOrderGpuHeuristics.CheckFactorsKernel));
Kernel convertToStandardKernel = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView1D<ulong, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>>(Pow2MontgomeryKernels.Pow2MontgomeryKernelConvertToStandard));
ConvertToStandardKernel = convertToStandardKernel;
ConvertToStandardKernelLauncher = convertToStandardKernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView1D<ulong, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>>>();
var heuristicCombinedTrialDivisionKernel = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, byte, ArrayView<int>, ulong, ulong, HeuristicCombinedGpuViews>(PrimeTesterKernels.HeuristicTrialCombinedDivisionKernel));
HeuristicCombinedTrialDivisionKernel = heuristicCombinedTrialDivisionKernel;
HeuristicCombinedTrialDivisionKernelLauncher = heuristicCombinedTrialDivisionKernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, byte, ArrayView<int>, ulong, ulong, HeuristicCombinedGpuViews>>();
KeepMontgomeryKernel = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView1D<ulong, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>>(Pow2MontgomeryKernels.Pow2MontgomeryKernelKeepMontgomery));
PollardRhoKernel = KernelUtil.GetKernel(accelerator.LoadStreamKernel<ulong, int, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<byte, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>(Pow2MontgomeryKernels.TryPollardRhoKernel));
Pow2ModWideKernel = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView1D<GpuUInt128, Stride1D.Dense>, GpuUInt128, ArrayView1D<GpuUInt128, Stride1D.Dense>>(PrimeOrderGpuHeuristics.Pow2ModKernelWide));
SharesFactorKernel = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<ulong>, ArrayView<byte>>(PrimeTesterKernels.SharesFactorKernel));
SmallPrimeFactorKernel = 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));
SmallPrimeSieveKernel = 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));
SpecialMaxKernel = KernelUtil.GetKernel(accelerator.LoadAutoGroupedStreamKernel<Index1D, ulong, ArrayView1D<ulong, Stride1D.Dense>, int, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ulong, Stride1D.Dense>>(PrimeOrderGpuHeuristics.EvaluateSpecialMaxCandidatesKernel));
}
}
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;
}
}
@@ -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;
+127
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@@ -0,0 +1,127 @@
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 readonly Context Context;
public readonly Accelerator Accelerator;
public PooledContext(KernelContainer kernels)
{
Context = SharedGpuContext.Context;
Accelerator = SharedGpuContext.Accelerator;
GpuStaticTableInitializer.EnsureStaticTables(kernels, Accelerator);
kernels.Dispose();
// 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.
PrimeTester.ClearGpuCaches(Accelerator);
// These resources are shared between GPU leases
// 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(GpuKernelPool.GetKernels()));
}
public static void WarmUpPool(int threadCount)
{
if (threadCount <= WarmedGpuContextCount)
{
return;
}
int toCreate = threadCount - WarmedGpuContextCount;
Console.WriteLine($"Warming up GPU context pool to {toCreate} contexts...");
var contexts = new PooledContext[toCreate];
var pool = GpuPool;
PooledContext context;
for (int i = 0; i < toCreate; i++)
{
KernelContainer kernels = GpuKernelPool.GetKernels();
context = new PooledContext(kernels);
contexts[i] = context;
pool.Enqueue(context);
}
WarmedGpuContextCount = threadCount;
}
public static void DisposeAll()
{
while (GpuPool.TryDequeue(out var gpu))
{
gpu.Dispose();
}
PrimeTester.DisposeGpuContexts();
WarmedGpuContextCount = 0;
}
private static void Return(PooledContext ctx)
{
ctx.Accelerator.Synchronize();
GpuPool.Enqueue(ctx);
}
public struct GpuContextLease
{
private PooledContext? _ctx;
private bool _disposed;
internal GpuContextLease(PooledContext ctx)
{
_ctx = ctx;
_disposed = false;
}
public Context Context => _ctx!.Context;
public Accelerator Accelerator => _ctx!.Accelerator;
public void Dispose()
{
if (_disposed)
{
return;
}
_disposed = true;
Return(_ctx!);
_ctx = null;
}
}
}
+165
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@@ -0,0 +1,165 @@
using System;
using System.Collections.Concurrent;
using ILGPU;
using ILGPU.Runtime;
using PerfectNumbers.Core;
using static PerfectNumbers.Core.Gpu.GpuContextPool;
namespace PerfectNumbers.Core.Gpu;
public sealed class GpuKernelLease
{
private static readonly ConcurrentQueue<GpuKernelLease> Pool = new();
private GpuContextLease? _gpu;
public KernelContainer Kernels;
private AcceleratorStream? _stream;
private GpuKernelLease(KernelContainer kernels)
{
Kernels = kernels;
}
internal static GpuKernelLease Rent(GpuContextLease gpu, KernelContainer kernels)
{
if (!Pool.TryDequeue(out var lease))
{
lease = new GpuKernelLease(kernels);
}
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, ArrayView1D<ulong, Stride1D.Dense>, int, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ushort, Stride1D.Dense>> SpecialMaxKernel
{
get
{
var accel = Accelerator;
return KernelContainer.InitOnce(ref Kernels!.SpecialMax, () =>
{
var loaded = accel.LoadAutoGroupedStreamKernel<Index1D, ulong, ArrayView1D<ulong, Stride1D.Dense>, int, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ushort, Stride1D.Dense>>(PrimeOrderGpuHeuristics.EvaluateSpecialMaxCandidatesKernel);
var kernel = KernelUtil.GetKernel(loaded);
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, ArrayView1D<ulong, Stride1D.Dense>, int, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ushort, 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;
Kernels?.Dispose();
GpuPrimeWorkLimiter.Release();
Pool.Enqueue(this);
}
}
+273 -183
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@@ -1,188 +1,189 @@
using PerfectNumbers.Core;
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;
public Action<AcceleratorStream, Index1D, ulong, ArrayView1D<ulong, Stride1D.Dense>, int, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>, ArrayView1D<ushort, 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>? 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<ulong, Stride1D.Dense>? SpecialMaxFactors;
public MemoryBuffer1D<ulong, Stride1D.Dense>? SpecialMaxCandidates;
public MemoryBuffer1D<ushort, Stride1D.Dense>? SpecialMaxResult;
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 void Dispose() => GpuKernelPool.Return(this);
}
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(
MemoryBuffer1D<uint, Stride1D.Dense> primes,
MemoryBuffer1D<ulong, Stride1D.Dense> squares,
int count)
{
public readonly MemoryBuffer1D<uint, Stride1D.Dense> Primes = primes;
public readonly MemoryBuffer1D<ulong, Stride1D.Dense> Squares = squares;
public readonly int Count = count;
public ArrayView1D<uint, Stride1D.Dense> PrimesView => Primes.View;
public ArrayView1D<ulong, Stride1D.Dense> SquaresView => Squares.View;
}
public readonly struct SmallPrimeFactorScratch(
MemoryBuffer1D<ulong, Stride1D.Dense> primeSlots,
MemoryBuffer1D<int, Stride1D.Dense> exponentSlots,
MemoryBuffer1D<int, Stride1D.Dense> countSlot,
MemoryBuffer1D<ulong, Stride1D.Dense> remainingSlot)
{
public readonly MemoryBuffer1D<ulong, Stride1D.Dense> PrimeSlots = primeSlots;
public readonly MemoryBuffer1D<int, Stride1D.Dense> ExponentSlots = exponentSlots;
public readonly MemoryBuffer1D<int, Stride1D.Dense> CountSlot = countSlot;
public readonly MemoryBuffer1D<ulong, Stride1D.Dense> RemainingSlot = remainingSlot;
public void Clear()
{
PrimeSlots.MemSetToZero();
ExponentSlots.MemSetToZero();
CountSlot.MemSetToZero();
RemainingSlot.MemSetToZero();
}
}
public readonly struct SpecialMaxScratch(
MemoryBuffer1D<ulong, Stride1D.Dense> factorValues,
MemoryBuffer1D<ulong, Stride1D.Dense> candidateValues,
MemoryBuffer1D<ushort, Stride1D.Dense> resultSlot)
{
public readonly MemoryBuffer1D<ulong, Stride1D.Dense> FactorValues = factorValues;
public readonly MemoryBuffer1D<ulong, Stride1D.Dense> CandidateValues = candidateValues;
public readonly MemoryBuffer1D<ushort, Stride1D.Dense> ResultSlot = resultSlot;
public ArrayView1D<ulong, Stride1D.Dense> FactorsView => FactorValues.View;
public ArrayView1D<ulong, Stride1D.Dense> CandidatesView => CandidateValues.View;
public ArrayView1D<ushort, Stride1D.Dense> ResultView => ResultSlot.View;
}
public class GpuKernelPool
{
[ThreadStatic]
private static KernelContainer[]? _pool;
private static readonly ConcurrentQueue<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
public static KernelContainer GetKernels() => KernelCache.TryDequeue(out var container)
? container
: new KernelContainer();
public static void Return(KernelContainer container) => KernelCache.Enqueue(container);
internal static void PreloadStaticTables(KernelContainer kernels, Accelerator accelerator)
{
if (target is { } value)
{
return value;
}
var newValue = valueFactory();
return Interlocked.CompareExchange(ref target, newValue, null) ?? newValue;
EnsureSmallCyclesOnDevice(kernels, accelerator);
EnsureSmallPrimesOnDevice(kernels, accelerator);
EnsureSmallPrimeFactorTables(kernels, accelerator);
}
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
internal static KernelContainer GetOrAddKernels(int acceleratorIndex, AcceleratorStream stream, KernelType kernelType)
{
var pool = _pool ??= [];
if (pool[acceleratorIndex] is not { } kernels)
{
kernels = new();
}
Accelerator accelerator = _accelerators[acceleratorIndex];
if (kernelType.HasFlag(KernelType.OrderKernelScan))
{
InitOrderKernelScan(accelerator, kernels);
}
if (kernelType.HasFlag(KernelType.Pow2ModKernelScan))
{
InitPow2ModKernelScan(accelerator, kernels);
}
if (kernelType.HasFlag(KernelType.IncrementalKernelScan))
{
InitIncrementalKernelScan(accelerator, kernels);
}
if (kernelType.HasFlag(KernelType.IncrementalOrderKernelScan))
{
IncrementalOrderKernelScan(accelerator, kernels);
}
if (kernelType.HasFlag(KernelType.Pow2ModOrderKernelScan))
{
InitPow2ModOrderKernelScan(accelerator, kernels);
}
PreloadStaticTables(accelerator, kernels, stream, kernelType);
pool[acceleratorIndex] = kernels;
return kernels;
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 kernel = KernelUtil.GetKernel(loaded);
return kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ulong, ulong, ArrayView<GpuUInt128>, ArrayView<ulong>>>();
});
}
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);
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>>>();
});
}
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);
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>>>();
});
}
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);
var kernel = KernelUtil.GetKernel(loaded);
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)
public static ArrayView1D<ulong, Stride1D.Dense> EnsureSmallCyclesOnDevice(KernelContainer kernels, Accelerator accelerator)
{
if (kernels.SmallCycles is { })
if (kernels.SmallCycles is { } buffer)
{
return;
return buffer.View;
}
var host = MersenneDivisorCycles.Shared.ExportSmallCyclesSnapshot();
MemoryBuffer1D<ulong, Stride1D.Dense>? device;
lock (accelerator)
{
device = accelerator.Allocate1D<ulong>(host.Length);
}
device.View.CopyFromCPU(stream, host);
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;
}
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)
public static ResiduePrimeViews EnsureSmallPrimesOnDevice(KernelContainer kernels, Accelerator accelerator)
{
if (kernels.SmallPrimesLastOne is { } &&
kernels.SmallPrimesLastSeven is { } &&
kernels.SmallPrimesPow2LastOne is { } &&
kernels.SmallPrimesPow2LastSeven is { })
if (kernels.SmallPrimesLastOne is { } lastOne &&
kernels.SmallPrimesLastSeven is { } lastSeven &&
kernels.SmallPrimesPow2LastOne is { } lastOnePow2 &&
kernels.SmallPrimesPow2LastSeven is { } lastSevenPow2)
{
return;
return new ResiduePrimeViews(lastOne.View, lastSeven.View, lastOnePow2.View, lastSevenPow2.View);
}
if (kernels.SmallPrimesLastOne is { } &&
kernels.SmallPrimesLastSeven is { } &&
kernels.SmallPrimesPow2LastOne is { } &&
kernels.SmallPrimesPow2LastSeven is { })
if (kernels.SmallPrimesLastOne is { } existingLastOne &&
kernels.SmallPrimesLastSeven is { } existingLastSeven &&
kernels.SmallPrimesPow2LastOne is { } existingLastOnePow2 &&
kernels.SmallPrimesPow2LastSeven is { } existingLastSevenPow2)
{
return;
return new ResiduePrimeViews(existingLastOne.View, existingLastSeven.View, existingLastOnePow2.View, existingLastSevenPow2.View);
}
var hostLastOne = PrimesGenerator.SmallPrimesLastOne;
@@ -190,27 +191,118 @@ public class GpuKernelPool
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;
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);
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;
return new ResiduePrimeViews(deviceLastOne.View, deviceLastSeven.View, deviceLastOnePow2.View, deviceLastSevenPow2.View);
}
public static SmallPrimeFactorTables EnsureSmallPrimeFactorTables(KernelContainer kernels, Accelerator accelerator)
{
if (kernels.SmallPrimeFactorsPrimes is { } primeBuffer && kernels.SmallPrimeFactorsSquares is { } squareBuffer)
{
return new SmallPrimeFactorTables(primeBuffer, squareBuffer, (int)primeBuffer.Length);
}
if (kernels.SmallPrimeFactorsPrimes is { } existingPrimes && kernels.SmallPrimeFactorsSquares is { } existingSquares)
{
return new SmallPrimeFactorTables(existingPrimes, existingSquares, (int)existingPrimes.Length);
}
var hostPrimes = PrimesGenerator.SmallPrimes;
var hostSquares = PrimesGenerator.SmallPrimesPow2;
var devicePrimes = accelerator.Allocate1D<uint>(hostPrimes.Length);
devicePrimes.View.CopyFromCPU(hostPrimes);
var deviceSquares = accelerator.Allocate1D<ulong>(hostSquares.Length);
deviceSquares.View.CopyFromCPU(hostSquares);
kernels.SmallPrimeFactorsPrimes = devicePrimes;
kernels.SmallPrimeFactorsSquares = deviceSquares;
return new SmallPrimeFactorTables(devicePrimes, deviceSquares, hostPrimes.Length);
}
public static SmallPrimeFactorScratch EnsureSmallPrimeFactorScratch(KernelContainer kernels, Accelerator accelerator, int slotCount)
{
MemoryBuffer1D<ulong, Stride1D.Dense>? primeSlots = kernels.SmallPrimeFactorPrimeSlots;
if (primeSlots is null || primeSlots.Length < slotCount)
{
primeSlots?.Dispose();
primeSlots = accelerator.Allocate1D<ulong>(slotCount);
kernels.SmallPrimeFactorPrimeSlots = primeSlots;
}
MemoryBuffer1D<int, Stride1D.Dense>? exponentSlots = kernels.SmallPrimeFactorExponentSlots;
if (exponentSlots is null || exponentSlots.Length < slotCount)
{
exponentSlots?.Dispose();
exponentSlots = accelerator.Allocate1D<int>(slotCount);
kernels.SmallPrimeFactorExponentSlots = exponentSlots;
}
MemoryBuffer1D<int, Stride1D.Dense>? countSlot = kernels.SmallPrimeFactorCountSlot;
if (countSlot is null)
{
countSlot = accelerator.Allocate1D<int>(1);
kernels.SmallPrimeFactorCountSlot = countSlot;
}
MemoryBuffer1D<ulong, Stride1D.Dense>? remainingSlot = kernels.SmallPrimeFactorRemainingSlot;
if (remainingSlot is null)
{
remainingSlot = accelerator.Allocate1D<ulong>(1);
kernels.SmallPrimeFactorRemainingSlot = remainingSlot;
}
return new SmallPrimeFactorScratch(primeSlots!, exponentSlots!, countSlot!, remainingSlot!);
}
public static SpecialMaxScratch EnsureSpecialMaxScratch(KernelContainer kernels, Accelerator accelerator, int factorCapacity)
{
MemoryBuffer1D<ulong, Stride1D.Dense>? factorValues = kernels.SpecialMaxFactors;
if (factorValues is null || factorValues.Length < factorCapacity)
{
factorValues?.Dispose();
factorValues = accelerator.Allocate1D<ulong>(factorCapacity);
kernels.SpecialMaxFactors = factorValues;
}
MemoryBuffer1D<ulong, Stride1D.Dense>? candidateValues = kernels.SpecialMaxCandidates;
if (candidateValues is null || candidateValues.Length < factorCapacity)
{
candidateValues?.Dispose();
candidateValues = accelerator.Allocate1D<ulong>(factorCapacity);
kernels.SpecialMaxCandidates = candidateValues;
}
MemoryBuffer1D<ushort, Stride1D.Dense>? resultSlot = kernels.SpecialMaxResult;
if (resultSlot is null)
{
resultSlot = accelerator.Allocate1D<ushort>(1);
kernels.SpecialMaxResult = resultSlot;
}
return new SpecialMaxScratch(factorValues!, candidateValues!, resultSlot!);
}
public static GpuKernelLease GetKernel(bool useGpuOrder)
{
GpuPrimeWorkLimiter.Acquire();
var gpu = Rent();
var kernels = GetKernels();
return GpuKernelLease.Rent(gpu, kernels);
}
/// <summary>
@@ -219,14 +311,12 @@ public class GpuKernelPool
/// <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);
var lease = GetKernel(useGpuOrder: true);
var accelerator = lease.Accelerator;
var stream = accelerator.CreateStream();
action(accelerator, stream);
stream.Synchronize();
stream.Dispose();
accelerator.Dispose();
// GpuPrimeWorkLimiter.Release();
lease.Dispose();
}
}
@@ -1,12 +1,15 @@
using System;
using System.Threading;
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 Acquire() => _semaphore.Wait();
public static void Release() => _semaphore.Release();
public static void SetLimit(int value)
{
@@ -0,0 +1,39 @@
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Runtime;
using PerfectNumbers.Core;
namespace PerfectNumbers.Core.Gpu;
internal static class GpuStaticTableInitializer
{
private static readonly ConcurrentDictionary<Accelerator, byte> Initialized = new(AcceleratorReferenceComparer.Instance);
internal static void EnsureStaticTables(KernelContainer kernels, Accelerator accelerator)
{
Initialized.GetOrAdd(accelerator, acc =>
{
PrimeTester.PrimeTesterGpuContextPool.EnsureStaticTables(kernels, acc);
GpuKernelPool.PreloadStaticTables(kernels, acc);
PrimeOrderGpuHeuristics.PreloadStaticTables( acc);
return 0;
});
}
private sealed class AcceleratorReferenceComparer : IEqualityComparer<Accelerator>
{
internal 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);
}
}
}
+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 +1,146 @@
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> CombinedDivisorsEnding1;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorsEnding3;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorsEnding7;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorsEnding9;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorSquaresEnding1;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorSquaresEnding3;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorSquaresEnding7;
public readonly ArrayView1D<ulong, Stride1D.Dense> CombinedDivisorSquaresEnding9;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupADivisors;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupADivisorSquares;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorsEnding1;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorSquaresEnding1;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorsEnding7;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorSquaresEnding7;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorsEnding9;
public readonly ArrayView1D<ulong, Stride1D.Dense> GroupBDivisorSquaresEnding9;
public HeuristicGpuDivisorTables(
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,
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)
{
CombinedDivisorsEnding1 = combinedDivisorsEnding1;
CombinedDivisorsEnding3 = combinedDivisorsEnding3;
CombinedDivisorsEnding7 = combinedDivisorsEnding7;
CombinedDivisorsEnding9 = combinedDivisorsEnding9;
CombinedDivisorSquaresEnding1 = combinedDivisorSquaresEnding1;
CombinedDivisorSquaresEnding3 = combinedDivisorSquaresEnding3;
CombinedDivisorSquaresEnding7 = combinedDivisorSquaresEnding7;
CombinedDivisorSquaresEnding9 = combinedDivisorSquaresEnding9;
GroupADivisors = groupADivisors;
GroupADivisorSquares = groupADivisorSquares;
GroupBDivisorsEnding1 = groupBDivisorsEnding1;
GroupBDivisorSquaresEnding1 = groupBDivisorSquaresEnding1;
GroupBDivisorsEnding7 = groupBDivisorsEnding7;
GroupBDivisorSquaresEnding7 = groupBDivisorSquaresEnding7;
GroupBDivisorsEnding9 = groupBDivisorsEnding9;
GroupBDivisorSquaresEnding9 = groupBDivisorSquaresEnding9;
}
[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,
};
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ArrayView1D<ulong, Stride1D.Dense> SelectCombinedSquares(byte ending)
{
return ending switch
{
1 => CombinedDivisorSquaresEnding1,
3 => CombinedDivisorSquaresEnding3,
7 => CombinedDivisorSquaresEnding7,
9 => CombinedDivisorSquaresEnding9,
_ => ArrayView1D<ulong, Stride1D.Dense>.Empty,
};
}
[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> SelectGroupBSquares(byte ending)
{
return ending switch
{
1 => GroupBDivisorSquaresEnding1,
7 => GroupBDivisorSquaresEnding7,
9 => GroupBDivisorSquaresEnding9,
_ => 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,
HeuristicGpuDivisorTableKind.Combined => SelectCombined(ending),
_ => ArrayView1D<ulong, Stride1D.Dense>.Empty,
};
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ArrayView1D<ulong, Stride1D.Dense> SelectDivisorSquares(HeuristicGpuDivisorTableKind kind, byte ending)
{
return kind switch
{
HeuristicGpuDivisorTableKind.GroupA => GroupADivisorSquares,
HeuristicGpuDivisorTableKind.GroupBEnding1 => GroupBDivisorSquaresEnding1,
HeuristicGpuDivisorTableKind.GroupBEnding7 => GroupBDivisorSquaresEnding7,
HeuristicGpuDivisorTableKind.GroupBEnding9 => GroupBDivisorSquaresEnding9,
HeuristicGpuDivisorTableKind.Combined => SelectCombinedSquares(ending),
_ => ArrayView1D<ulong, Stride1D.Dense>.Empty,
};
}
internal static void InitializeShared(in HeuristicGpuDivisorTables 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
@@ -1,5 +1,6 @@
using ILGPU;
using ILGPU.Runtime;
using PerfectNumbers.Core;
namespace PerfectNumbers.Core.Gpu;
@@ -12,7 +13,7 @@ internal static partial class PrimeOrderGpuHeuristics
int factorCount,
MontgomeryDivisorData divisor,
ArrayView1D<ulong, Stride1D.Dense> candidates,
ArrayView1D<ulong, Stride1D.Dense> resultOut)
ArrayView1D<ushort, Stride1D.Dense> resultOut)
{
if (index != 0)
{
@@ -61,7 +62,7 @@ internal static partial class PrimeOrderGpuHeuristics
var stepper = new ExponentRemainderStepperGpu(divisorPartial);
if (stepper.InitializeIsUnityGpu(candidates[0]))
{
Atomic.Exchange(ref resultOut[0], 0);
resultOut[0] = 0;
return;
}
@@ -69,11 +70,11 @@ internal static partial class PrimeOrderGpuHeuristics
{
if (stepper.ComputeNextIsUnityGpu(candidates[i]))
{
Atomic.Exchange(ref resultOut[0], 0);
resultOut[0] = 0;
return;
}
}
Atomic.Exchange(ref resultOut[0], 1);
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;
@@ -78,49 +78,17 @@ 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,
HeuristicGpuDivisorTableKind tableKind,
HeuristicGroupABGpuViews tables)
HeuristicGpuDivisorTables tables)
{
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 = tables.SelectDivisors(tableKind, nMod10);
ArrayView1D<ulong, Stride1D.Dense> divisorSquares = tables.SelectDivisorSquares(tableKind, nMod10);
int divisorLength = (int)divisorSquares.Length;
int threadIndex = index;
@@ -153,37 +121,35 @@ 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(gpuLease.Kernels, accelerator);
ResiduePrimeViews primeViews = default;
if (_kernelType == GpuKernelType.Pow2Mod)
{
primeViews = GpuKernelPool.GetSmallPrimesOnDevice(kernels);
primeViews = GpuKernelPool.EnsureSmallPrimesOnDevice(gpuLease.Kernels, 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);
ArrayPool<ulong>.Shared.Return(orderArray);
orderBuffer.Dispose();
// GpuPrimeWorkLimiter.Release();
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;
}
GpuPrimeWorkLimiter.Acquire();
bool result;
if (exponent >= 128UL)
{
if (!TryGetNttParameters(exponent, out var nttMod, out var primitiveRoot))
{
GpuPrimeWorkLimiter.Release();
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();
GpuPrimeWorkLimiter.Release();
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;
}
}
@@ -7,46 +7,36 @@ public class MersenneNumberOrderGpuTester(GpuKernelType kernelType, bool useGpuO
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)
{
// GpuPrimeWorkLimiter.Acquire();
// var accelerator = SharedGpuContext.Accelerator;
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 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
KernelContainer kernels = GpuKernelPool.GetOrAddKernels(acceleratorIndex, stream, KernelType.Pow2ModOrderKernelScan | KernelType.IncrementalOrderKernelScan);
var kernel = _kernelType switch
{
GpuKernelType.Pow2Mod => kernels.Pow2ModOrder!,
_ => kernels.IncrementalOrder!,
GpuKernelType.Pow2Mod => gpuLease.Pow2ModOrderKernel,
_ => gpuLease.IncrementalOrderKernel,
};
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.
}
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);
UInt128 remaining;
int currentSize;
int found = 0;
var smallCyclesView = GpuKernelPool.GetSmallCyclesOnDevice(kernels);
var smallCyclesView = GpuKernelPool.EnsureSmallCyclesOnDevice(gpuLease.Kernels, accelerator);
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);
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
@@ -56,13 +46,11 @@ public class MersenneNumberOrderGpuTester(GpuKernelType kernelType, bool useGpuO
var kernelArgs = new ResidueAutomatonArgs(q0m10, step10, q0m8, step8, q0m3, step3, q0m5, step5);
// 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
);
kernel(stream, currentSize, exponent, (GpuUInt128)twoP, (GpuUInt128)kStart, last, divMul,
kernelArgs, foundBuffer.View, smallCyclesView);
foundBuffer.View.CopyToCPU(stream, ref found, 1);
stream.Synchronize();
foundBuffer.View.CopyToCPU(ref found, 1);
if (found != 0)
{
Volatile.Write(ref isPrime, false);
@@ -72,8 +60,7 @@ public class MersenneNumberOrderGpuTester(GpuKernelType kernelType, bool useGpuO
kStart += (UInt128)currentSize;
}
stream.Dispose();
foundBuffer.Dispose();
// GpuPrimeWorkLimiter.Release();
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 +12,187 @@ 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)
{
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;
// 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];
// Monitor.Enter(gpuLease.ExecutionLock);
var stream = accelerator.CreateStream();
var kernel = GetPow2ModKernel(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);
var gpuKernels = GpuKernelPool.GetKernels();
var orderBuffer = resources.OrderBuffer;
ulong[] orderArray = resources.OrderArray;
int batchSize = resources.Capacity;
var orderBuffer = resources.OrderBuffer;
ulong[] orderArray = resources.OrderArray;
int batchSize = resources.Capacity;
// 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);
// Ensure device has small cycles and primes tables for in-kernel lookup
var smallCyclesView = GpuKernelPool.EnsureSmallCyclesOnDevice(gpuKernels, accelerator);
ResiduePrimeViews primeViews = GpuKernelPool.EnsureSmallPrimesOnDevice(gpuKernels, accelerator);
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();
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();
GpuUInt128 twoPGpu = (GpuUInt128)twoP;
UInt128 batchSize128 = (UInt128)batchSize;
UInt128 fullBatchStep = twoP * batchSize128;
UInt128 q = twoP * kStart + UInt128.One;
GpuUInt128 twoPGpu = (GpuUInt128)twoP;
UInt128 batchSize128 = (UInt128)batchSize;
UInt128 fullBatchStep = twoP * batchSize128;
UInt128 q = twoP * kStart + UInt128.One;
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);
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);
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);
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);
kernel(stream, currentSize, exponent, twoPGpu, (GpuUInt128)kStart, last, 0UL,
kernelArgs, orderBuffer.View, smallCyclesView, primeViews.LastOne, primeViews.LastSeven, primeViews.LastOnePow2, primeViews.LastSevenPow2);
kernel(stream, currentSize, exponent, twoPGpu, (GpuUInt128)kStart, last, 0UL,
kernelArgs, orderBuffer.View, smallCyclesView, primeViews.LastOne, primeViews.LastSeven, primeViews.LastOnePow2, primeViews.LastSevenPow2);
orderBuffer.View.CopyToCPU(stream, ref ordersRef, currentSize);
stream.Synchronize();
if (!Volatile.Read(ref isPrime))
{
break;
}
stream.Synchronize();
orderBuffer.View.CopyToCPU(ref ordersRef, currentSize);
if (!Volatile.Read(ref isPrime))
{
break;
}
bool compositeFound = false;
for (int i = 0; i < currentSize; i++)
{
if (orders[i] != 0UL)
{
Volatile.Write(ref isPrime, false);
compositeFound = true;
break;
}
}
bool compositeFound = false;
for (int i = 0; i < currentSize; i++)
{
if (orders[i] != 0UL)
{
Volatile.Write(ref isPrime, false);
compositeFound = true;
break;
}
}
if (compositeFound)
{
break;
}
if (compositeFound)
{
break;
}
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.
}
}
}
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(resources);
stream.Dispose();
ReturnResources(accelerator, resources);
stream.Dispose();
// Monitor.Exit(gpuLease.ExecutionLock);
gpuKernels.Dispose();
// GpuPrimeWorkLimiter.Release();
}
ReturnAccelerator(gpuLease);
GpuPrimeWorkLimiter.Release();
}
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)
{
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);
});
var pool = _pow2ModKernel ?? [];
if (pool.TryGetValue(accelerator, out var cached))
{
return cached;
}
private GpuContextPool.GpuContextLease RentAccelerator()
{
if (_acceleratorPool.TryTake(out var lease))
{
return lease;
}
cached = CreatePow2ModKernel(accelerator);
pool[accelerator] = cached;
return cached;
}
return GpuContextPool.Rent();
}
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);
private void ReturnAccelerator(GpuContextPool.GpuContextLease lease) => _acceleratorPool.Add(lease);
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 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)
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)
{
OrderBuffer = accelerator.Allocate1D<ulong>(Capacity);
}
// The caller always overwrites the required elements. We don't need to worry about clearing the output buffer.
// resources.OrderBuffer.MemSetToZero();
return resources;
}
OrderArray = ThreadStaticPools.UlongPool.Rent(Capacity);
}
resources.Dispose();
}
internal void EnsureCapacity(Accelerator accelerator, int capacity)
{
if (OrderBuffer.Length >= capacity)
{
return;
}
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;
}
OrderBuffer.Dispose();
ThreadStaticPools.UlongPool.Return(OrderArray);
private void ReturnResources(Accelerator accelerator, ResidueResources resources) =>
_resourcePools.GetOrAdd(accelerator, static _ => new ConcurrentBag<ResidueResources>()).Add(resources);
// lock (accelerator)
{
OrderBuffer = accelerator.Allocate1D<ulong>(capacity);
}
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);
}
OrderArray = ThreadStaticPools.UlongPool.Rent(capacity);
Capacity = capacity;
}
internal MemoryBuffer1D<ulong, Stride1D.Dense> OrderBuffer { get; }
internal MemoryBuffer1D<ulong, Stride1D.Dense> OrderBuffer { get; private set; }
internal ulong[] OrderArray { get; }
internal ulong[] OrderArray { get; private set; }
internal int Capacity { get; }
internal int Capacity { get; private set; }
public void Dispose()
{
OrderBuffer.Dispose();
ArrayPool<ulong>.Shared.Return(OrderArray, clearArray: false);
}
}
public void Dispose()
{
OrderBuffer.Dispose();
ThreadStaticPools.UlongPool.Return(OrderArray, clearArray: false);
}
}
private sealed class AcceleratorReferenceComparer : IEqualityComparer<Accelerator>
{
public static AcceleratorReferenceComparer Instance { get; } = new();
private sealed class AcceleratorReferenceComparer : IEqualityComparer<Accelerator>
{
public static AcceleratorReferenceComparer Instance { get; } = new();
public bool Equals(Accelerator? x, Accelerator? y) => ReferenceEquals(x, y);
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);
}
}
}
+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)
@@ -1,97 +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;
var kernel = gpu.KeepMontgomeryKernel;
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 = kernel.CreateLauncherDelegate<Action<AcceleratorStream, Index1D, ArrayView1D<ulong, Stride1D.Dense>, MontgomeryDivisorData, ArrayView1D<ulong, Stride1D.Dense>>>();
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;
}
@@ -1,16 +0,0 @@
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
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;
}
+9 -19
View File
@@ -1,29 +1,19 @@
using System.Runtime.CompilerServices;
using System;
using System.Threading;
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
public static class SharedGpuContext
internal static class SharedGpuContext
{
public static readonly Context Context = Context.CreateDefault();
public static readonly Device Device = Context.GetPreferredDevice(false);
private static readonly Lazy<Context> s_context = new(() => ILGPU.Context.CreateDefault(), LazyThreadSafetyMode.ExecutionAndPublication);
private static readonly Lazy<Device> s_device = new(() => s_context.Value.GetPreferredDevice(false), LazyThreadSafetyMode.ExecutionAndPublication);
private static readonly Lazy<Accelerator> s_accelerator = new(() => s_device.Value.CreateAccelerator(s_context.Value), LazyThreadSafetyMode.ExecutionAndPublication);
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static Accelerator CreateAccelerator() => Device.CreateAccelerator(Context);
}
internal static Context Context => s_context.Value;
public readonly struct GpuContext
{
public readonly Context Context;
public readonly Device Device;
internal static Device Device => s_device.Value;
public GpuContext()
{
var context = Context.CreateDefault();
Context = context;
Device = context.GetPreferredDevice(false);
}
public Accelerator CreateAccelerator() => Device.CreateAccelerator(Context);
internal static Accelerator Accelerator => s_accelerator.Value;
}
@@ -1,34 +0,0 @@
using System.Runtime.CompilerServices;
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
public readonly struct SmallPrimeFactorGpuTables
{
private static readonly Accelerator[] _accelerators = AcceleratorPool.Shared.Accelerators;
private static readonly SmallPrimeFactorGpuTables?[] _sharedTables = new SmallPrimeFactorGpuTables?[PerfectNumberConstants.RollingAccelerators];
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static SmallPrimeFactorGpuTables? GetStaticTables(int acceleratorIndex) => _sharedTables[acceleratorIndex];
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static void WarmUp(int acceleratorIndex, AcceleratorStream stream) => _sharedTables[acceleratorIndex] = new SmallPrimeFactorGpuTables(_accelerators[acceleratorIndex], stream);
public readonly MemoryBuffer1D<uint, Stride1D.Dense> Primes;
public readonly MemoryBuffer1D<ulong, Stride1D.Dense> Squares;
public readonly int Count;
public SmallPrimeFactorGpuTables(Accelerator accelerator, AcceleratorStream stream)
{
var hostPrimes = PrimesGenerator.SmallPrimes;
var hostSquares = PrimesGenerator.SmallPrimesPow2;
MemoryBuffer1D<uint, Stride1D.Dense>? devicePrimes = accelerator.Allocate1D(stream, hostPrimes);
MemoryBuffer1D<ulong, Stride1D.Dense>? deviceSquares = accelerator.Allocate1D(stream, hostSquares);
Primes = devicePrimes;
Squares = deviceSquares;
Count = hostPrimes.Length;
}
}
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