Files
stgsharp/StgSharp.Mathematics/Numeric/MatrixParallel.cs
T

209 lines
7.4 KiB
C#

//-----------------------------------------------------------------------
// -----------------------------------------------------------------------
// file="MatrixParallel"
// Project: StgSharp
// AuthorGroup: Nitload Space
// Copyright (c) Nitload Space. All rights reserved.
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in all
// copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
//
// -----------------------------------------------------------------------
// -----------------------------------------------------------------------
using StgSharp.Collections;
using System;
using System.Collections.Generic;
using System.Diagnostics.CodeAnalysis;
using System.Runtime.CompilerServices;
using System.Threading;
namespace StgSharp.Mathematics.Numeric
{
/*
* Thread wrapping to accelerate matrix operations by dividing threads into groups (pool).
* For M pool, each containing an average of N threads, we satisfy the condition M * N = T - 4,
* where T is the total thread count of the CPU. Typically, for modern consumer CPUs, T is around 16.
* For simplicity, let M * N = 16.
*
* The total time complexity for publishing tasks is O(M + N):
* - O(M) accounts for distributing tasks across M pool.
* - O(N) accounts for threads within each wrap fetching tasks from the wrap queue.
*
* Using the inequality Sqrt(M * N) <= (M + N) / 2 (derived from the arithmetic-geometric mean inequality),
* the optimal configuration occurs when M = N. For M * N = 16, this gives M = N = 4.
*
* To ensure compatibility across a wide range of CPU architectures,
* we allow each wrap to contain either 3 or 4 threads, providing flexibility while maintaining efficiency.
*/
public static partial class MatrixParallel
{
private static Thread[] _threads;
private static readonly (int a, int b)[] LookupTable = [ (1, 1), // 7
(0, 2), // 8 (no non-zero solution)
(3, 0), // 9 (no non-zero solution)
(2, 1), // 10
(1, 2), // 11
(0, 3), // 12 (no non-zero solution)
(3, 1), // 13
(2, 2), // 14
(1, 3), // 15
(4, 1), // 16
(3, 2), // 17
(2, 3), // 18
(1, 4), // 19
(4, 2), // 20
];
private static bool _meaningful;
private static volatile int RemainThreadCount = 0;
private static readonly object _lock = new();
private static ThreadPriority _AfterWork = ThreadPriority.Lowest;
public static bool SupportParallel { get; } = Environment.ProcessorCount > 6;
public static bool IsParallelMeaningful => Environment.ProcessorCount > 6 && IsInitialized;
private static bool IsInitialized { get; set; } = false;
private static Queue<IntPtr> LeaderTask { get; set; }
public static void EndParallel()
{
Monitor.Exit(_lock);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static (int count_3, int count_4) FastDecompose(int c)
{
if (c < 7) {
return (0, 0);
}
int t = c - 7;
int k = t / 14;
int d = t % 14;
(int a0, int b0) = LookupTable[d];
return (a0 + (2 * k), b0 + (2 * k));
}
public static void Init()
{
if (IsInitialized) {
return;
}
MatrixParallelFactory.Init();
if (!SupportParallel)
{
IsInitialized = true;
return;
}
int count = Environment.ProcessorCount - 4;
count = count == 5 ? 4 : count;
_threads = new Thread[count];
if (count < 6)
{
if (count == 3)
{
Pool = new(3, [ new MatrixParallelWrap(0, count) ]);
(LargeWrapCount, SmallWrapCount) = (0, 1);
} else
{
count = 4;
Pool = new(4, [ new MatrixParallelWrap(0, count) ]);
(LargeWrapCount, SmallWrapCount) = (1, 0);
}
} else if (count == 6)
{
Pool = new(6, [ new MatrixParallelWrap(0, 3), new MatrixParallelWrap(3, 3) ]);
(LargeWrapCount, SmallWrapCount) = (0, 2);
} else
{
(int _3wrap, int _4wrap) = FastDecompose(count);
CapacityFixedStack<MatrixParallelWrap> stack = new(_4wrap + _3wrap);
int id = 0, idx = 0;
for (; idx < _3wrap; idx++, id += 3) {
stack.Push(new MatrixParallelWrap(idx, 3));
}
for (; idx < _3wrap + _4wrap; idx++, id += 4) {
stack.Push(new MatrixParallelWrap(id, 4));
}
Pool = new MatrixParallelPool(count, stack);
}
IsInitialized = true;
}
public static void LaunchParallel(IEnumerable<MatrixParallelWrap> wraps, SleepMode afterWork)
{
RemainThreadCount = _threads.Length;
_AfterWork = (ThreadPriority)afterWork;
SetAllWrap(wraps);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static unsafe void MatrixParallelLeaderWork()
{
MatrixParallelWrap.ExecuteTaskPackage(LeaderTask);
_ = Interlocked.Decrement(ref RemainThreadCount);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static void ResetThreadCount()
{
RemainThreadCount = _threads.Length;
}
public static void SetAllWrap(IEnumerable<MatrixParallelWrap> wraps)
{
ResetThreadCount();
foreach (MatrixParallelWrap item in wraps) {
item.SchedulerReset.Set();
}
}
#region wrap field
private static MatrixParallelPool Pool;
private static int LargeWrapCount;
private static int SmallWrapCount;
public static MatrixParallelPool LeadParallel()
{
#if NET9_0_OR_GREATER
#else
Monitor.Enter(_lock);
#endif
return Pool;
}
public static void ReleaseParallelLeadership(ref MatrixParallelPool pool)
{
#if NET9_0_OR_GREATER
#else
Monitor.Exit(_lock);
#endif
pool = null!;
}
#endregion
}
}