Initial work on killer moves. Add soft tm (gains 41.8 +/- 22.0)

Chess/nim.cfg

@@ -1,6 +1,6 @@
 --cc:clang
 -o:"bin/nimfish"
--d:danger
+-d:debug
 --passL:"-flto -lmimalloc"
 --passC:"-flto -march=native -mtune=native"
 -d:useMalloc

Chess/nimfish/nimfishpkg/search.nim

@@ -30,6 +30,7 @@ import threading/smartptrs
 
 type
     HistoryTable* = array[PieceColor.White..PieceColor.Black, array[Square(0)..Square(63), array[Square(0)..Square(63), Score]]]
+    KillersTable* = seq[array[2, Move]]
     SearchManager* = ref object
         ## A simple state storage
         ## for our search
@@ -46,15 +47,15 @@ type
         searchMoves: seq[Move]
         previousBestMove: Move
         transpositionTable: SharedPtr[TTable]
-        # Storage for our history euristic
         history: SharedPtr[HistoryTable]
+        killers: SharedPtr[KillersTable]
 
 
 proc newSearchManager*(board: Chessboard, transpositions: SharedPtr[TTable], stopFlag, searchFlag: SharedPtr[Atomic[bool]],
-                       history: SharedPtr[HistoryTable]): SearchManager =
+                       history: SharedPtr[HistoryTable], killers: SharedPtr[KillersTable]): SearchManager =
     new(result)
     result = SearchManager(board: board, bestMoveRoot: nullMove(), transpositionTable: transpositions, stopFlag: stopFlag,
-                           searchFlag: searchFlag, history: history)
+                           searchFlag: searchFlag, history: history, killers: killers)
 
 
 proc isSearching*(self: SearchManager): bool =
@@ -71,19 +72,24 @@ proc stop*(self: SearchManager) =
 
 
 proc getEstimatedMoveScore(self: SearchManager, move: Move): Score =
-    ## Returns an estimated static score for the move
+    ## Returns an estimated static score for the move used
+    ## during move ordering
     result = Score(0)
     let 
         sideToMove = self.board.position.sideToMove
         nonSideToMove = sideToMove.opposite()
+
     if self.previousBestMove != nullMove() and move == self.previousBestMove:
         return highestEval() + 1
+
     let query = self.transpositionTable[].get(self.board.position.zobristKey)
     if query.success and query.entry.bestMove != nullMove() and query.entry.bestMove == move:
         return highestEval() + 1
+
     if not move.isCapture():
         # History euristic bonus
         result += self.history[][sideToMove][move.startSquare][move.targetSquare]
+
     if move.isCapture():
         # Implementation of MVVLVA: Most Valuable Victim Least Valuable Attacker
         # We prioritize moves that capture the most valuable pieces, and as a
@@ -91,6 +97,7 @@ proc getEstimatedMoveScore(self: SearchManager, move: Move): Score =
         # is why we multiply the score of the captured piece by 10, to give
         # it priority)
         result += 10 * self.board.position.getPieceScore(move.targetSquare) - self.board.position.getPieceScore(move.startSquare)
+
     if move.isPromotion():
         # Promotions are a good idea to search first
         var piece: Piece
@@ -106,6 +113,7 @@ proc getEstimatedMoveScore(self: SearchManager, move: Move): Score =
             else:
                 discard  # Unreachable
         result += self.board.position.getPieceScore(piece, move.targetSquare)
+
     if self.board.position.getPawnAttacks(move.targetSquare, nonSideToMove) != 0:
         # Moving on a square attacked by an enemy pawn is _usually_ a very bad
         # idea. Assume the piece is lost and give a malus based on the fact that
@@ -342,8 +350,8 @@ proc findBestMove*(self: SearchManager, timeRemaining, increment: int64, maxDept
     
     # Apparently negative remaining time is a thing. Welp
     let 
-        maxSearchTime = max(1, (timeRemaining div 20) + (increment div 2))
+        maxSearchTime = max(1, (timeRemaining div 10) + (increment div 2))
-        softLimit = max(1, (timeRemaining div 30) + (increment div 2))
+        softLimit = max(1, maxSearchTime div 3)
     self.bestMoveRoot = nullMove()
     result = self.bestMoveRoot
     self.maxNodes = maxNodes
@@ -357,6 +365,8 @@ proc findBestMove*(self: SearchManager, timeRemaining, increment: int64, maxDept
     self.searchFlag[].store(true)
     # Iterative deepening loop
     for i in 1..maxDepth:
+        if self.killers[].len() < i:
+            self.killers[].add([nullMove(), nullMove()])
         # Search the previous best move first
         self.previousBestMove = self.bestMoveRoot
         self.search(i, 0, lowestEval(), highestEval())
@@ -369,17 +379,10 @@ proc findBestMove*(self: SearchManager, timeRemaining, increment: int64, maxDept
         # Soft time management: don't start a new search iteration
         # if the soft limit has expired, as it is unlikely to complete
         # anyway
-        when defined(softTM):
         if self.shouldStop() or getMonoTime() >= self.softLimit:
             self.log(i - 1)
             break
         else:
             self.log(i)
-        else:
-            if self.shouldStop():
-                self.log(i - 1)
-                break
-            else:
-                self.log(i)
     self.searchFlag[].store(false)
     self.stopFlag[].store(false)

Chess/nimfish/nimfishpkg/uci.nim

@@ -31,13 +31,23 @@ type
     UCISession = object
         ## A UCI session
         debug: bool
+        # Previously reached positions
         history: seq[Position]
+        # The current position
         position: Position
+        # Atomic boolean flag to interrupt the search
         stopFlag: SharedPtr[Atomic[bool]]
+        # Atomic search flag used to know whether a search
+        # is in progress
         searchFlag: SharedPtr[Atomic[bool]]
+        # Size of the transposition table (in megabytes)
         hashTableSize: uint64
+        # The transposition table
         transpositionTable: SharedPtr[TTable]
+        # Storage for our history heuristic
         historyTable: SharedPtr[HistoryTable]
+        # Storage for our killer move heuristic
+        killerMoves: SharedPtr[KillersTable]
     
     UCICommandType = enum
         ## A UCI command type enumeration
@@ -305,14 +315,15 @@ proc bestMove(args: tuple[session: UCISession, command: UCICommand]) {.thread.}
     ## Finds the best move in the current position
     setControlCHook(proc () {.noconv.} = quit(0))
 
-    {.cast(gcsafe).}:
     # Yes yes nim sure this isn't gcsafe. Now stfu and spawn a thread
+    {.cast(gcsafe).}:
         var session = args.session
         var board = newChessboard()
         board.position = session.position
         board.positions = session.history
         let command = args.command
-        var searcher = newSearchManager(board, session.transpositionTable, session.stopFlag, session.searchFlag, session.historyTable)
+        var searcher = newSearchManager(board, session.transpositionTable, session.stopFlag,
+                                        session.searchFlag, session.historyTable, session.killerMoves)
         var 
             timeRemaining = (if session.position.sideToMove == White: command.wtime else: command.btime)
             increment = (if session.position.sideToMove == White: command.winc else: command.binc)
@@ -339,6 +350,7 @@ proc startUCISession* =
     session.searchFlag = newSharedPtr(Atomic[bool])
     session.transpositionTable[] = newTranspositionTable(session.hashTableSize * 1024 * 1024)
     session.historyTable = newSharedPtr(HistoryTable)
+    session.killerMoves = newSharedPtr(KillersTable)
     session.stopFlag[].store(false)
     # Fun fact, nim doesn't collect the memory of thread vars. Another stupid fucking design pitfall
     # of nim's AWESOME threading model. Someone is getting a pipebomb in their mailbox about this, mark