Files
even-perfect-numbers-scanner/PerfectNumbers.Core/PrimeTester.cs
T

536 lines
17 KiB
C#

using System;
using System.Buffers;
using System.Collections.Concurrent;
using System.Numerics;
using System.Runtime.CompilerServices;
using System.Threading;
using ILGPU;
using ILGPU.Algorithms;
using ILGPU.Runtime;
using PerfectNumbers.Core.Gpu;
namespace PerfectNumbers.Core;
public sealed class PrimeTester
{
public PrimeTester(bool useInternal = false)
{
}
[ThreadStatic]
private static PrimeTester? _tester;
public static PrimeTester Exclusive => _tester ??= new();
public bool IsPrime(ulong n, CancellationToken ct)
{
return IsPrimeInternal(n, ct);
}
public static bool IsPrimeGpu(ulong n)
{
return Exclusive.IsPrimeGpu(n, CancellationToken.None);
}
public static bool IsPrimeGpu(ulong n, ulong limit, byte nMod10)
{
return Exclusive.IsPrimeGpu(n, CancellationToken.None);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public bool IsPrimeGpu(ulong n, CancellationToken ct)
{
return IsPrimeGpuFallback(n, ct);
}
public static bool IsPrimeGpuFallback(ulong n, CancellationToken ct)
{
bool forceCpu = GpuContextPool.ForceCpu;
Span<ulong> one = stackalloc ulong[1];
Span<byte> outFlags = stackalloc byte[1];
one[0] = n;
outFlags[0] = 0;
if (!forceCpu)
{
IsPrimeBatchGpu(one, outFlags);
}
bool belowGpuRange = n < 31UL;
bool gpuReportedPrime = !forceCpu && !belowGpuRange && outFlags[0] != 0;
bool requiresCpuFallback = forceCpu || belowGpuRange || !gpuReportedPrime;
return requiresCpuFallback ? IsPrimeInternal(n, ct) : true;
}
public static bool IsPrimeInternal(ulong n, CancellationToken ct)
{
bool isTwo = n == 2UL;
bool isOdd = (n & 1UL) != 0UL;
ulong mod5 = n % 5UL;
bool divisibleByFive = n > 5UL && mod5 == 0UL;
bool result = n >= 2UL && (isTwo || isOdd) && !divisibleByFive;
bool requiresTrialDivision = result && n >= 7UL && !isTwo;
if (requiresTrialDivision)
{
bool sharesMaxExponentFactor = n.Mod10() == 1UL && SharesFactorWithMaxExponent(n);
result &= !sharesMaxExponentFactor;
if (result)
{
var smallPrimeDivisorsLength = PrimesGenerator.SmallPrimes.Length;
uint[] smallPrimeDivisors = PrimesGenerator.SmallPrimes;
ulong[] smallPrimeDivisorsMul = PrimesGenerator.SmallPrimesPow2;
for (int i = 0; i < smallPrimeDivisorsLength; i++)
{
if (smallPrimeDivisorsMul[i] > n)
{
break;
}
if (n % smallPrimeDivisors[i] == 0)
{
result = false;
break;
}
}
}
}
return result;
}
internal readonly struct HeuristicDivisorCandidate
{
private readonly HeuristicPrimeTester.HeuristicDivisorCandidate _inner;
internal HeuristicDivisorCandidate(HeuristicPrimeTester.HeuristicDivisorCandidate inner)
{
_inner = inner;
}
public ulong Value => _inner.Value;
public HeuristicPrimeTester.HeuristicDivisorGroup Group => _inner.Group;
public byte Ending => _inner.Ending;
public byte PriorityIndex => _inner.PriorityIndex;
public ushort WheelResidue => _inner.WheelResidue;
internal HeuristicPrimeTester.HeuristicDivisorCandidate AsHeuristic() => _inner;
}
internal readonly struct HeuristicDivisorPreparation
{
private readonly HeuristicPrimeTester.HeuristicDivisorPreparation _inner;
internal HeuristicDivisorPreparation(HeuristicPrimeTester.HeuristicDivisorPreparation inner)
{
_inner = inner;
}
public HeuristicDivisorCandidate Candidate => new(_inner.Candidate);
public MontgomeryDivisorData DivisorData => _inner.DivisorData;
public ulong CycleLengthHint => _inner.CycleLengthHint;
public bool HasCycleLengthHint => _inner.HasCycleLengthHint;
public bool RequiresCycleComputation => _inner.RequiresCycleComputation;
internal HeuristicPrimeTester.HeuristicDivisorPreparation AsHeuristic() => _inner;
}
internal ref struct MersenneHeuristicDivisorEnumerator
{
private HeuristicPrimeTester.MersenneHeuristicDivisorEnumerator _inner;
public MersenneHeuristicDivisorEnumerator(ulong exponent, ulong maxDivisor)
{
_inner = HeuristicPrimeTester.CreateMersenneDivisorEnumerator(exponent, maxDivisor);
}
public ulong ProcessedCount => _inner.ProcessedCount;
public ulong LastDivisor => _inner.LastDivisor;
public bool Exhausted => _inner.Exhausted;
public bool TryGetNext(out HeuristicDivisorCandidate candidate)
{
if (_inner.TryGetNext(out var innerCandidate))
{
candidate = new HeuristicDivisorCandidate(innerCandidate);
return true;
}
candidate = default;
return false;
}
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static MersenneHeuristicDivisorEnumerator CreateMersenneDivisorEnumerator(ulong exponent, ulong maxDivisor)
{
return new MersenneHeuristicDivisorEnumerator(exponent, maxDivisor);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static HeuristicDivisorPreparation PrepareHeuristicDivisor(in HeuristicDivisorCandidate candidate)
{
var innerCandidate = candidate.AsHeuristic();
var preparation = HeuristicPrimeTester.PrepareHeuristicDivisor(in innerCandidate);
return new HeuristicDivisorPreparation(preparation);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static ulong ResolveHeuristicCycleLength(
ulong exponent,
in HeuristicDivisorPreparation preparation,
out bool cycleFromHint,
out bool cycleComputed,
out bool primeOrderFailed)
{
var innerPreparation = preparation.AsHeuristic();
return HeuristicPrimeTester.ResolveHeuristicCycleLength(
exponent,
in innerPreparation,
out cycleFromHint,
out cycleComputed,
out primeOrderFailed);
}
public static int GpuBatchSize { get; set; } = 262_144;
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static void IsPrimeBatchGpu(ReadOnlySpan<ulong> values, Span<byte> results)
{
var limiter = GpuPrimeWorkLimiter.Acquire();
var gpu = PrimeTesterGpuContextPool.Rent();
try
{
var accelerator = gpu.Accelerator;
var state = GpuKernelState.GetOrCreate(accelerator);
int totalLength = values.Length;
int batchSize = Math.Max(1, GpuBatchSize);
lock (gpu.ExecutionLock)
{
var scratch = state.RentScratch(batchSize, accelerator);
var input = scratch.Input;
var output = scratch.Output;
ulong[] temp = ArrayPool<ulong>.Shared.Rent(batchSize);
try
{
int pos = 0;
while (pos < totalLength)
{
int remaining = totalLength - pos;
int count = remaining > batchSize ? batchSize : remaining;
values.Slice(pos, count).CopyTo(temp);
input.View.CopyFromCPU(ref temp[0], count);
state.Kernel(count, input.View, state.DevicePrimes.View, output.View);
accelerator.Synchronize();
output.View.CopyToCPU(ref results[pos], count);
pos += count;
}
}
finally
{
ArrayPool<ulong>.Shared.Return(temp);
state.ReturnScratch(scratch);
}
}
}
finally
{
gpu.Dispose();
limiter.Dispose();
}
}
internal static class PrimeTesterGpuContextPool
{
internal sealed class PooledContext : IDisposable
{
private bool _disposed;
public Context Context { get; }
public Accelerator Accelerator { get; }
public object ExecutionLock { get; } = new();
public PooledContext()
{
Context = Context.CreateDefault();
Accelerator = Context.GetPreferredDevice(false).CreateAccelerator(Context);
}
public void Dispose()
{
if (_disposed)
{
return;
}
PrimeTester.ClearGpuCaches(Accelerator);
Accelerator.Dispose();
Context.Dispose();
_disposed = true;
}
}
private static readonly ConcurrentQueue<PooledContext> Pool = new();
private static readonly object CreationLock = new();
internal static PrimeTesterGpuContextLease Rent()
{
if (Pool.TryDequeue(out var ctx))
{
return new PrimeTesterGpuContextLease(ctx);
}
lock (CreationLock)
{
return new PrimeTesterGpuContextLease(new PooledContext());
}
}
internal static void DisposeAll()
{
while (Pool.TryDequeue(out var ctx))
{
ctx.Dispose();
}
}
private static void Return(PooledContext ctx)
{
ctx.Accelerator.Synchronize();
Pool.Enqueue(ctx);
}
internal struct PrimeTesterGpuContextLease : IDisposable
{
private PooledContext? _ctx;
internal PrimeTesterGpuContextLease(PooledContext ctx)
{
_ctx = ctx;
}
public Accelerator Accelerator => _ctx!.Accelerator;
public object ExecutionLock => _ctx!.ExecutionLock;
public void Dispose()
{
if (_ctx is { } ctx)
{
Return(ctx);
_ctx = null;
}
}
}
}
// Per-accelerator GPU state for prime sieve (kernel + uploaded primes).
internal sealed class KernelState
{
public Action<Index1D, ArrayView<ulong>, ArrayView<uint>, ArrayView<byte>> Kernel { get; }
public Action<Index1D, ArrayView<ulong>, ulong, ArrayView<byte>> HeuristicTrialDivisionKernel { get; }
public MemoryBuffer1D<uint, Stride1D.Dense> DevicePrimes { get; }
private readonly Accelerator _accel;
private readonly System.Collections.Concurrent.ConcurrentBag<ScratchBuffers> _scratchPool = [];
// TODO: Replace this ConcurrentBag with the lock-free ring buffer variant validated in
// GpuModularArithmeticBenchmarks so renting scratch buffers stops contending on the bag's internal locks when
// thousands of GPU batches execute per second.
public KernelState(Accelerator accelerator)
{
_accel = accelerator;
// Compile once per accelerator and upload primes once.
Kernel = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<ulong>, ArrayView<uint>, ArrayView<byte>>(PrimeTesterKernels.SmallPrimeSieveKernel);
HeuristicTrialDivisionKernel = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<ulong>, ulong, ArrayView<byte>>(PrimeTesterKernels.HeuristicTrialDivisionKernel);
var primes = PrimesGenerator.SmallPrimes;
DevicePrimes = accelerator.Allocate1D<uint>(primes.Length);
DevicePrimes.View.CopyFromCPU(primes);
}
internal sealed class ScratchBuffers : IDisposable
{
public MemoryBuffer1D<ulong, Stride1D.Dense> Input { get; private set; }
public MemoryBuffer1D<byte, Stride1D.Dense> Output { get; private set; }
public int Capacity { get; private set; }
public ScratchBuffers(Accelerator accel, int capacity)
{
Capacity = Math.Max(1, capacity);
Input = accel.Allocate1D<ulong>(Capacity);
Output = accel.Allocate1D<byte>(Capacity);
}
public void Dispose()
{
Output.Dispose();
Input.Dispose();
}
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ScratchBuffers RentScratch(int minCapacity, Accelerator accel)
{
minCapacity = Math.Max(1, minCapacity);
while (_scratchPool.TryTake(out var sb))
{
if (sb.Capacity >= minCapacity)
{
return sb;
}
sb.Dispose();
}
return new ScratchBuffers(accel, minCapacity);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public void ReturnScratch(ScratchBuffers scratch)
{
_scratchPool.Add(scratch);
}
public void Clear()
{
while (_scratchPool.TryTake(out var sb))
{
sb.Dispose();
}
DevicePrimes.Dispose();
}
}
internal static class GpuKernelState
{
// Map accelerator to cached state; use Lazy to serialize kernel creation
private static readonly System.Collections.Concurrent.ConcurrentDictionary<Accelerator, Lazy<KernelState>> States = new();
// TODO: Prewarm this per-accelerator cache during startup (and reuse a simple array keyed by accelerator index)
// once the kernel pool exposes deterministic ordering; the Lazy wrappers showed measurable overhead in the
// GpuModularArithmeticBenchmarks hot path.
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static KernelState GetOrCreate(Accelerator accelerator)
{
var lazy = States.GetOrAdd(
accelerator,
acc => new Lazy<KernelState>(() => new KernelState(acc), System.Threading.LazyThreadSafetyMode.ExecutionAndPublication));
return lazy.Value;
}
public static void Clear(Accelerator accelerator)
{
if (States.TryRemove(accelerator, out var lazy))
{
if (lazy.IsValueCreated)
{
var state = lazy.Value;
state.Clear();
}
}
}
}
// Expose cache clearing for accelerator disposal coordination
public static void ClearGpuCaches(Accelerator accelerator)
{
GpuKernelState.Clear(accelerator);
}
internal static void DisposeGpuContexts()
{
PrimeTesterGpuContextPool.DisposeAll();
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static bool SharesFactorWithMaxExponent(ulong n)
{
// TODO: Replace this on-the-fly GCD probe with the cached factor table derived from
// ResidueComputationBenchmarks so divisor-cycle metadata can short-circuit the test
// instead of recomputing binary GCD for every candidate.
ulong m = (ulong)BitOperations.Log2(n);
return BinaryGcd(n, m) != 1UL;
}
internal static void SharesFactorWithMaxExponentBatch(ReadOnlySpan<ulong> values, Span<byte> results)
{
// TODO: Route this batch helper through the shared GPU kernel pool from
// GpuUInt128BinaryGcdBenchmarks so we reuse cached kernels, pinned host buffers,
// and divisor-cycle staging instead of allocating new device buffers per call.
var gpu = PrimeTesterGpuContextPool.Rent();
var accelerator = gpu.Accelerator;
var kernel = accelerator.LoadAutoGroupedStreamKernel<Index1D, ArrayView<ulong>, ArrayView<byte>>(PrimeTesterKernels.SharesFactorKernel);
int length = values.Length;
var inputBuffer = accelerator.Allocate1D<ulong>(length);
var resultBuffer = accelerator.Allocate1D<byte>(length);
ulong[] temp = ArrayPool<ulong>.Shared.Rent(length);
values.CopyTo(temp);
inputBuffer.View.CopyFromCPU(ref temp[0], length);
kernel(length, inputBuffer.View, resultBuffer.View);
accelerator.Synchronize();
resultBuffer.View.CopyToCPU(ref results[0], length);
ArrayPool<ulong>.Shared.Return(temp);
resultBuffer.Dispose();
inputBuffer.Dispose();
gpu.Dispose();
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static ulong BinaryGcd(ulong u, ulong v)
{
// TODO: Swap this handwritten binary GCD for the optimized helper measured in
// GpuUInt128BinaryGcdBenchmarks so CPU callers share the faster subtract-less
// ladder once the common implementation is promoted into PerfectNumbers.Core.
if (u == 0UL)
{
return v;
}
if (v == 0UL)
{
return u;
}
int shift = BitOperations.TrailingZeroCount(u | v);
u >>= BitOperations.TrailingZeroCount(u);
do
{
v >>= BitOperations.TrailingZeroCount(v);
if (u > v)
{
(u, v) = (v, u);
}
v -= u;
}
while (v != 0UL);
return u << shift;
}
}