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refactor(bot): split NNUE into shared weights and per-thread evaluator

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Prerequisite for parallel search. NNUE held all state on one instance:
the immutable transposed L1 weight matrix alongside the mutable
accumulator stack, scratch buffers and eval cache. That made concurrent
eval calls corrupt shared buffers.

Extract the read-only parameters into NNUEWeights (heavy to build, safe
to share). NNUE now owns only per-instance mutable buffers and references
the shared weights, so many evaluators can run in parallel over one weight
matrix without duplicating it. Single-instance behaviour is unchanged —
EvaluationNNUE still uses one evaluator, so play is identical.

Also applies scalafmt alignment to the MopUp files.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Janis
2026-06-30 12:12:26 +02:00
parent 7136803c7e
commit b72e8ec017
4 changed files with 37 additions and 15 deletions
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modules/official-bots/src/test/scala/de/nowchess/bot/MopUpTest.scala
+2 -2
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@@ -11,8 +11,8 @@ class MopUpTest extends AnyFunSuite with Matchers:
private def ctx(turn: Color, pieces: (Square, Piece)*): GameContext =
GameContext.initial.withBoard(Board(pieces.toMap)).withTurn(turn)
private val wk = Square(File.E, Rank.R1) -> Piece.WhiteKing
private val wq = Square(File.D, Rank.R1) -> Piece.WhiteQueen
private val wk = Square(File.E, Rank.R1) -> Piece.WhiteKing
private val wq = Square(File.D, Rank.R1) -> Piece.WhiteQueen
private val bkCorner = Square(File.H, Rank.R8) -> Piece.BlackKing
private val bkCenter = Square(File.D, Rank.R4) -> Piece.BlackKing