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even-perfect-numbers-scanner/PerfectNumbers.Core/Gpu/GpuContextPool.cs
T

162 lines
4.0 KiB
C#

using System.Collections.Concurrent;
using ILGPU;
using ILGPU.Runtime;
namespace PerfectNumbers.Core.Gpu;
public static class GpuContextPool
{
private static readonly bool PoolingEnabled = true;
// 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.)
public static bool ForceCpu { get; set; } = false;
internal sealed class PooledContext
{
private bool disposed;
public Context Context { get; }
public Accelerator Accelerator { get; }
public bool IsCpu { get; }
public object ExecutionLock { get; } = new();
public PooledContext(bool preferCpu)
{
Context = Context.CreateDefault();
Accelerator = Context.GetPreferredDevice(preferCpu).CreateAccelerator(Context);
IsCpu = Accelerator.AcceleratorType == AcceleratorType.CPU;
// 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()
{
if (disposed)
{
return;
}
// 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);
Accelerator.Dispose();
Context.Dispose();
disposed = true;
}
}
private static readonly ConcurrentQueue<PooledContext> CpuPool = new();
private static readonly ConcurrentQueue<PooledContext> GpuPool = new();
private static readonly object CreationLock = new();
public static GpuContextLease Rent()
{
return RentPreferred(ForceCpu);
}
// Allows callers to choose CPU/GPU per use-case, decoupled from ForceCpu.
public static GpuContextLease RentPreferred(bool preferCpu)
{
if (PoolingEnabled)
{
if (preferCpu && CpuPool.TryDequeue(out var cpu))
{
return new GpuContextLease(cpu, CreationLock);
}
if (!preferCpu && GpuPool.TryDequeue(out var gpu))
{
return new GpuContextLease(gpu, CreationLock);
}
}
// Serialize accelerator creation to avoid concurrent CL device/stream setup across threads.
lock (CreationLock)
{
return new GpuContextLease(new PooledContext(preferCpu), CreationLock);
}
}
public static void DisposeAll()
{
if (!PoolingEnabled)
{
return;
}
while (CpuPool.TryDequeue(out var cpu))
{
cpu.Dispose();
}
while (GpuPool.TryDequeue(out var gpu))
{
gpu.Dispose();
}
}
private static void Return(PooledContext ctx)
{
if (PoolingEnabled)
{
ctx.Accelerator.Synchronize();
if (ctx.IsCpu)
{
CpuPool.Enqueue(ctx);
}
else
{
GpuPool.Enqueue(ctx);
}
}
else
{
lock (CreationLock)
{
ctx.Dispose();
}
}
}
public struct GpuContextLease
{
private readonly PooledContext _ctx;
private bool disposed;
internal GpuContextLease(PooledContext ctx, object kernelInitLock)
{
_ctx = ctx;
KernelInitLock = kernelInitLock;
}
public Context Context => _ctx.Context;
public Accelerator Accelerator => _ctx.Accelerator;
public object KernelInitLock { get; }
public object ExecutionLock => _ctx.ExecutionLock;
public void Dispose()
{
if (disposed)
{
return;
}
Return(_ctx);
disposed = true;
}
}
}