back to matrix, but trouble in combining L4 predict with matrixparallelqueue
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//-----------------------------------------------------------------------
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// -----------------------------------------------------------------------
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// file="MatrixCompute.Sequential"
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// Project: StgSharp
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// AuthorGroup: Nitload
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// Copyright (c) Nitload. All rights reserved.
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//
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// Permission is hereby granted, free of charge, to any person obtaining a copy
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// of this software and associated documentation files (the "Software"), to deal
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// in the Software without restriction, including without limitation the rights
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// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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// copies of the Software, and to permit persons to whom the Software is
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// furnished to do so, subject to the following conditions:
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//
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// The above copyright notice and this permission notice shall be included in all
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// copies or substantial portions of the Software.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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// SOFTWARE.
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//
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// -----------------------------------------------------------------------
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// -----------------------------------------------------------------------
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using StgSharp.HighPerformance.Memory;
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using StgSharp.Mathematics.Numeric.Runtime;
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Text;
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using System.Threading.Tasks;
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using unsafe MkProc = delegate* unmanaged[Cdecl]<StgSharp.Mathematics.Internal.MatrixParallelTask*, void>;
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namespace StgSharp.Mathematics.Numeric.Linear
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{
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public static unsafe partial class MatrixCompute
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{
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public static void Add(
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Matrix<float> left,
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Matrix<float> right,
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Matrix<float> ans
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)
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{
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ArgumentNullException.ThrowIfNull(left, nameof(left));
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ArgumentNullException.ThrowIfNull(right, nameof(right));
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ArgumentNullException.ThrowIfNull(ans, nameof(ans));
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if ((left.ColumnLength != right.ColumnLength) ||
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(left.RowLength != right.RowLength) ||
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(left.ColumnLength != ans.ColumnLength) ||
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(left.RowLength != ans.RowLength)) {
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throw new MatrixDimensionMismatchException<float>(
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left, right, ans
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);
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}
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MatrixElementType f32 = MatrixElementType.F32;
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long count = ((long)left.KernelColumnLength) * left.KernelRowLength;
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MatrixKernel<float>* leftPtr = left.Buffer;
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MatrixKernel<float>* rightPtr = right.Buffer;
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MatrixKernel<float>* ansPtr = ans.Buffer;
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MkProc add = (MkProc)NumericalModule.GlobalContext.
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mat_mk[f32.IntrinsicNode].
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Get(MatrixIntrinsicHandle.Add);
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MatrixParallelTask* t = stackalloc MatrixParallelTask[1];
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t->Mat1 = (MatrixKernel*)leftPtr;
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t->Mat2 = (MatrixKernel*)rightPtr;
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t->Mat3 = (MatrixKernel*)ansPtr;
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t->ElementType = MatrixElementType.F64;
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t->Scalar.Data<long>(0) = count;
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if (count <= 256)
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{
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add(t);
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// .buffer_add(leftPtr, rightPtr, ansPtr, count);
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return;
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} else if (count <= 1024)
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{
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MatrixParallelThread[] pool = MatrixParallel.LeadParallel(1);
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add(t);
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MatrixParallel.ReturnParallelResources(ref pool);
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return;
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}
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MatrixParallelWrap taskGroup = MatrixParallel.ScheduleTask<SequentialPredictor>((nuint)add, t);
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taskGroup.LaunchParallel(SleepMode.DeepSleep);
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taskGroup.Dispose();
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return;
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}
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private sealed class SequentialPredictor : MatrixPredictor<SequentialPredictor>
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{
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public override bool Predict(
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Span<CacheLinePrediction> node,
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out int count
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)
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{
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throw new NotImplementedException();
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}
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public override void Prefetch(
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nuint origin,
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ulong policy,
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Span<byte> cache
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)
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{
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throw new NotImplementedException();
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}
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public override void WriteBack(
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nuint origin,
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ulong policy,
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ReadOnlySpan<byte> cache
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)
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{
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throw new NotImplementedException();
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}
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}
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}
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}
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