General-purpose computing on graphics processing units
General-purpose computing on graphics processing units (GPGPU, or less often GPGP) is the use of a graphics processing unit (GPU), which typically handles computation only for computer graphics, to perform computation in applications traditionally handled by the central processing unit (CPU). The use of multiple video cards in one computer, or large numbers of graphics chips, further parallelizes the already parallel nature of graphics processing.
General-purpose computing on graphics processing units - Wikipedia Jump to content From Wikipedia, the free encyclopedia Use of a GPU for computations typically assigned to CPUs This article needs additional citations for verification . Please help improve this article by adding citations to reliable sources . Unsourced material may be challenged and removed. Find sources:   "General-purpose computing on graphics processing units"  –  news   · newspapers   · books   · scholar   · JSTOR ( February 2022 ) ( Learn how and when to remove this message ) General-pu
saved by
related reading
- CUDA - Wikipediaen.wikipedia.org
- CUDA C++ Programming Guide (Legacy) — CUDA C++ Programming Guidedocs.nvidia.com
- GitHub - adam-maj/tiny-gpu: A minimal GPU design in Verilog to learn how GPUs work from the ground up · GitHubgithub.com
- Execution Model - SLING user documentationdoc.sling.si
- GPU Performance Background User's Guide - NVIDIA Docsdocs.nvidia.com
- Inside NVIDIA GPUs: Anatomy of high performance matmul kernels - Aleksa Gordićaleksagordic.com
- How to Think About GPUs | How To Scale Your Modeljax-ml.github.io
- CUDA Programming Guide — CUDA Programming Guidedocs.nvidia.com
- Demystifying GPU Compute Architectures - by Babbagethechipletter.substack.com
- How to Optimize a CUDA Matmul Kernel for cuBLAS-like Performance: a Worklogsiboehm.com
- On the GPU Memory Hierarchygytis.co
- The Best GPUs for Deep Learning in 2023 — An In-depth Analysistimdettmers.com