mat
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@@ -30,6 +30,7 @@ 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.Runtime.CompilerServices;
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using System.Text;
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using System.Threading.Tasks;
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@@ -71,34 +72,45 @@ namespace StgSharp.Mathematics.Numeric.Linear
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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->ElementType = f32;
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t->ComputeHandle = MatrixIntrinsicHandle.Add;
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t->Scalar.Data<long>(0) = count;
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SequentialOperation(t, count);
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private static void SequentialOperation(
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MatrixParallelTask* task,
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long count
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)
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{
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MatrixElementType elementType = task->ElementType;
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MatrixParallelThread[] pool;
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MkProc op = (MkProc)NumericalModule.GlobalContext.
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mat_mk[elementType.IntrinsicNode].
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Get(task->ComputeHandle);
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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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op(task);
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return;
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} else if (count <= 1024)
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{
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pool = MatrixParallel.LeadParallel(1);
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add(t);
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op(task);
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MatrixParallel.ReturnParallelResources(ref pool);
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return;
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}
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pool = MatrixParallel.LeadParallel((int)(count / 1024));
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MatrixParallelWrap taskGroup = MatrixParallel.ScheduleTask<SequentialPredictor>(pool, t);
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pool = MatrixParallel.LeadParallel(count / 1024);
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MatrixParallelWrap taskGroup = MatrixParallel.ScheduleTask<SequentialPredictor>(pool, task);
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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 struct SequentialPredictor : IMatrixPredictor<SequentialPredictor>
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{
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public static PredictPolicy Policy => PredictPolicy.Sequential;
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public bool Predict(
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Span<CacheLinePrediction> node,
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out int count
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