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GPU
,→2020 ...: link to Chinese gpus
=GPU in Computer Chess=
There are some in main approaches four ways how to using use a GPU for chess:
* As an accelerator in [[Leela_Chess_Zero|Lc0]]: run a neural network for position evaluation on GPU
* Offload the search in [[Zeta|Zeta]]: run a parallel game tree search with move generation and position evaluation on GPU
* As a hybrid in [http://www.talkchess.com/forum3/viewtopic.php?t=64983&start=4#p729152 perft_gpu]: expand the game tree to a certain degree on CPU and offload to GPU to compute the sub-tree
* Neural network training such as [https://github.com/glinscott/nnue-pytorch Stockfish NNUE trainer in Pytorch]<ref>[http://www.talkchess.com/forum3/viewtopic.php?f=7&t=75724 Pytorch NNUE training] by [[Gary Linscott]], [[CCC]], November 08, 2020</ref> or [https://github.com/LeelaChessZero/lczero-training Lc0 TensorFlow Training]
=GPU Chess Engines=
==AMD Matrix Cores==
: AMD released 2020 its server-class [https://www.amd.com/system/files/documents/amd-cdna-whitepaper.pdf CDNA] architecture with Matrix Cores which support MFMA (matrix-fused-multiply-add) operations on various data types like INT8, FP16, BF16, FP32. AMD's CDNA 2 architecture adds FP64 optimized throughput for matrix operations. AMD's RDNA 3 architecture features dedicated AI tensor operation acceleration. AMD's CDNA 3 architecture adds support for FP8 and sparse matrix data (sparsity).
==Intel XMX Cores==
: Intel added XMX, Xe Matrix eXtensions, cores to some of the [https://en.wikipedia.org/wiki/Intel_Xe Intel Xe] GPU series, like [https://en.wikipedia.org/wiki/Intel_Arc#Alchemist Arc Alchemist] and [https://www.intel.com/content/www/us/en/products/sku/232876/intel-data-center-gpu-max-1100/specifications.html Intel Data Center GPU Max Series].
=Host-Device Latencies=
* [https://www.amd.com/system/files/documents/rdna-whitepaper.pdf RDNA Whitepaper]
* [https://gpuopen.com/wp-content/uploads/2019/08/RDNA_Architecture_public.pdf Architecture Slide Deck]
* [https://gpuopen.com/wp-content/uploads/2019/08/RDNA_Shader_ISA_5August2019.pdf RDNA Instruction SetArchitecture]
=== Vega GCN 5th gen ===
* [https://www.techpowerup.com/gpu-specs/docs/amd-vega-architecture.pdf Architecture Whitepaper]
* [https://wwwdeveloper.amd.com/system/fileswp-content/TechDocsresources/vega-7nm-shader-instruction-set-architectureVega_Shader_ISA_28July2017.pdf Vega Instruction SetArchitecture]
=== Polaris GCN 4th gen ===
* [https://www.amd.com/system/files/documents/polaris-whitepaper.pdf Architecture Whitepaper]
* [https://developer.amd.com/wordpress/media/2013/12/AMD_GCN3_Instruction_Set_Architecture_rev1.1.pdf GCN3/4 Instruction Set Architecture]
=== Southern Islands GCN 1st gen ===
* [https://en.wikipedia.org/wiki/Radeon_HD_7000_series AMD Radeon HD 7000 on Wikipedia]
* [https://www.amd.wpenginepowered.com/wordpresscontent/dam/amd/en/mediadocuments/2013radeon-tech-docs/10programmer-references/si_programming_guide_v2.pdf Southern Islands Programming Guide]* [https://developer.amd.wpenginepowered.com/wordpress/media/20132012/0712/AMD_Southern_Islands_Instruction_Set_Architecture1AMD_Southern_Islands_Instruction_Set_Architecture.pdf Southern Islands Instruction Set Architecture]
== Apple ==
* [https://en.wikipedia.org/wiki/List_of_Nvidia_graphics_processing_units List of Nvidia graphics processing units on Wikipedia]
=== Grace Hopper Superchip ===
The Nvidia GH200 Grace Hopper Superchip was unveiled August, 2023 and combines the Nvidia Grace CPU ([[ARM|ARM v9]]) and Nvidia Hopper GPU architectures via NVLink to deliver a CPU+GPU coherent memory model for accelerated AI and HPC applications.
* [https://resources.nvidia.com/en-us-grace-cpu/grace-hopper-superchip NVIDIA Grace Hopper Superchip Data Sheet]
* [https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper NVIDIA Grace Hopper Superchip Architecture Whitepaper]
=== Ada Lovelace Architecture ===
The [https://en.wikipedia.org/wiki/Ada_Lovelace_(microarchitecture) Ada Lovelace microarchitecture] was announced on September 20, 2022, featuring 4th-generation Tensor Cores with FP8, FP16, BF16, TF32 and sparsity acceleration.
* [https://talkchess.com/forum3/viewtopic.php?f=2&t=77097 GPU rumors 2021] by [[Srdja Matovic]], [[CCC]], April 16, 2021
* [https://www.talkchess.com/forum3/viewtopic.php?f=7&t=79078 Comparison of all known Sliding lookup algorithms <nowiki>[CUDA]</nowiki>] by [[Daniel Infuehr]], [[CCC]], January 08, 2022 » [[Sliding Piece Attacks]]
* [https://talkchess.com/forum3/viewtopic.php?f=7&t=72566&p=955538#p955538 Re: China boosts in silicon...] by [[Srdja Matovic]], [[CCC]], January 13, 2024
=External Links=
