636501ab86
Muddled the code too much, and only gave a marginal performance improvement in the grand scheme of things. Other ways to parallelize MCTS will be nicer to implement and could yield better results.
63 lines
2.0 KiB
C#
63 lines
2.0 KiB
C#
using System.Diagnostics.Contracts;
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using System.Numerics;
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using System.Runtime.CompilerServices;
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namespace Craftimizer.Solver.Crafty;
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// Adapted from https://github.com/dtao/ConcurrentList/blob/4fcf1c76e93021a41af5abb2d61a63caeba2adad/ConcurrentList/ConcurrentList.cs
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public struct NodeScoresBuffer
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{
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public sealed class ScoresBatch
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{
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public Memory<float> ScoreSum;
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public Memory<float> MaxScore;
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public Memory<int> Visits;
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public ScoresBatch()
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{
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ScoreSum = new float[BatchSize];
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MaxScore = new float[BatchSize];
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Visits = new int[BatchSize];
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}
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}
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// Technically 25, but it's very unlikely to actually get to there.
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// The benchmark reaches 20 at most, but here we have a little leeway just in case.
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private const int MaxSize = 24;
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private static readonly int BatchSize = Vector<float>.Count;
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private static readonly int BatchSizeBits = int.Log2(BatchSize);
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private static readonly int BatchSizeMask = BatchSize - 1;
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private static readonly int BatchCount = MaxSize / BatchSize;
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public ScoresBatch[] Data;
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public int Count { get; private set; }
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public void Add()
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{
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Data ??= new ScoresBatch[BatchCount];
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var idx = Count++;
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var (arrayIdx, _) = GetArrayIndex(idx);
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Data[arrayIdx] ??= new();
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}
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public readonly void Visit((int arrayIdx, int subIdx) at, float score)
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{
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Data[at.arrayIdx].ScoreSum.Span[at.subIdx] += score;
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Data[at.arrayIdx].MaxScore.Span[at.subIdx] = Math.Max(Data[at.arrayIdx].MaxScore.Span[at.subIdx], score);
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Data[at.arrayIdx].Visits.Span[at.subIdx]++;
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}
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public readonly int GetVisits((int arrayIdx, int subIdx) at) =>
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Data[at.arrayIdx].Visits.Span[at.subIdx];
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[Pure]
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private static (int arrayIdx, int subIdx) GetArrayIndex(int idx) =>
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(idx >> BatchSizeBits, idx & BatchSizeMask);
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}
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