Changes

GPUs are much more suited than CPUs to implement and train [[Neural Networks#Convolutional|Convolutional Neural Networks]] (CNN), and were therefore also responsible for the [[Deep Learning|deep learning]] boom, also affecting game playing programs combining CNN with [[Monte-Carlo Tree Search|MCTS]], as pioneered by [[Google]] [[DeepMind|DeepMind's]] [[AlphaGo]] and [[AlphaZero]] entities in [[Go]], [[Shogi]] and [[Chess]] using [https://en.wikipedia.org/wiki/Tensor_processing_unit TPUs], and the open source projects [[Leela Zero]] headed by [[Gian-Carlo Pascutto]] for [[Go]] and its [[Leela Chess Zero]] adaption.

The market is split into two categories, integrated and discrete GPUs. The first being the most important by quantity, the second by performance. Discrete GPUs are divided as consumer brands for playing 3D games, professional brands for CAD/CGI programs and server brands for big-data and number-crunching workloads. Each brand offering different feature sets in driver, VRAM, or computation abilities.

* [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]

=== Vega GCN 5th gen ===

* [https://www.techpowerup.com/gpu-specs/docs/amd-vega-architecture.pdf Architecture Whitepaper]

=== Polaris GCN 4th gen ===

The Mali GPU variants can be found on various systems on chips (SoCs) from different vendors. Since Midgard (2012) with unified-shader-model OpenCL support is offered.

* [https://developer.arm.com/documentation/101574/latest Bifrost and Valhall OpenCL Developer Guide]

Imagination Technologies licenses PowerVR IP to third parties (most notable Apple) used for system on a chip (SoC) designs. Since Series5 SGX OpenCL support via licensees is available.

=Chess Engines=