Editing Parallel computing (section)

=====General-purpose computing on graphics processing units (GPGPU)=====
{{main|GPGPU}}

[[File:NvidiaTesla.jpg|right|thumbnail|Nvidia's [[Nvidia Tesla|Tesla GPGPU card]]]]

General-purpose computing on [[graphics processing unit]]s (GPGPU) is a fairly recent trend in computer engineering research. GPUs are co-processors that have been heavily optimized for [[computer graphics]] processing.<ref>Boggan, Sha'Kia and Daniel M. Pressel (August 2007). [https://discover.dtic.mil/results/?q=ARL-SR-154 GPUs: An Emerging Platform for General-Purpose Computation]  (PDF). ARL-SR-154, U.S. Army Research Lab. Retrieved on November 7, 2007.</ref> Computer graphics processing is a field dominated by data parallel operations—particularly [[linear algebra]] [[Matrix (mathematics)|matrix]] operations.

In the early days, GPGPU programs used the normal graphics APIs for executing programs. However, several new programming languages and platforms have been built to do general purpose computation on GPUs with both [[Nvidia]] and [[AMD]] releasing programming environments with [[CUDA]] and [[AMD FireStream#Software Development Kit|Stream SDK]] respectively. Other GPU programming languages include [[BrookGPU]], [[PeakStream]], and [[RapidMind]]. Nvidia has also released specific products for computation in their [[Nvidia Tesla|Tesla series]]. The technology consortium Khronos Group has released the [[OpenCL]] specification, which is a framework for writing programs that execute across platforms consisting of CPUs and GPUs. [[AMD]], [[Apple Inc.|Apple]], [[Intel]], [[Nvidia]] and others are supporting [[OpenCL]].