and you'll likely be memory bound at that point, but hey it was fun trying! ![]() You're looking for ILP ( Instruction Level Parallelism) which is typically measured as IPC ( Instructions Per Cycle), where the "s" in "Instructions" is a clue that several are expected.Īs an example, a CPU with 4 Arithmetic Units may be able to process 4 Arithmetic IPC, and therefore if you only get an IPL of 2.0 IPS, you're only using 50% of your CPU resources.Īnd of course there's SIMD too, so you may be able to get the CPU to execute several SIMD instructions per cycle. Modern x86_64 processors can retire several instructions simultaneously, if they don't have interdependencies. If you like the code consider buying me a coffee :). C++ is an awesome language for performance! - Please read the Article and Source if you are interested! This approach is 6-8x faster than the currently leading movegenerator written in C.Īnyways I dont want the post be too long. This is the slowest position and most positions get around 2 Billion nodes per second and 1 thread. That is 119 Million in 85ms or just about 1400 Million nodes per second for the staring position. The code does not need to evaluate a Enpassant move if the enemy didnt push - or any castling move if its not possible to castle anymore. First ever complete Template gamestate.Solves all checks and pins with only and / not instructions - and a few lookups for king / knight - sliders! No "If" needed for 99% of chess Original legal move generator - almost completely branchless.Fastest bmi2 Pext intrinsics slider lookup _pextu64().First ever Make-Unmake free Chess Movegenertaor.Instead of generating a list - this movegenerator decides the instant it sees a possible move what to do with it! Castling and Enpassant gets compiled away by if constexpr when its not on the board - or possible anymore! Instead of having a movelist - we pass a small template inlined function which is the callback for every possible move. I also was able to implement a visitor pattern in the first ever chess related piece of code. Thats the fun part: If the movegenerator generates this kind of code - you can move multiple pieces at once. ![]() This will clear the bit on the from square. Moving a piece on a bitboard looks like this: Piece ^= (from | to). Things like where a piece can move become extremely pleasant to write:uint64_t move = Seemap & EnemyOrEmpty & noCheck Which normally would need 8 if statements to generate - but can be done in 2 branchless instruction with a bitbord. Same for all other 11 piecetypes.ĭoing it this way enables all 8 pawns to walk forward like this: (WPawn << 8) & Empty. So we can define a Bitbord of all pawns to be just one single uint64_t. Ideally, you could provide some code for python-chess with which I'm using right now.So for the last 2½ I was obsessed with the move generation problem of chess.Ĭhess is such a beautiful programming problem to solve - since one board contains exactly 64 squares. So has anybody experience with Stockfish and can guide me in the correct direction on how to optimize the search for the best possible move. could drastically improve the search results for the optimal move. This lets me to believe that just given Stockfish the search depth is not the best way. Most often Stockfish achieves a draw and can win sometimes with white. Because when using Stockfish 11 with depth 20 it can barely win against the computer of level 10 which is rumored to have a rating of around 2600. I want to look deeper into how to achieve the optimal move. I also found this stack overflow article: Is the depth of a chess engine its strength? but most of the links there are dead. ![]() Unfortunately that paper is from 2013 and no specific engine is named, but it can be assumed that results are nowadays a little higher. ![]() In this paper ( ) they analyze the correlation between search depth and rating of the engine the essential result is basically: Of course the quality of the move depends on the search depth. Stockfish 11 is stated to have an approximated rating of about 3550. At the moment I set the depth of the search operation for the optimal move with (depth=engine_depth) I use python-chess to integrate the Stockfish engine in my simulation. I use the stockfish engine to generate the optimal moves in an simulated chess game.
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