Back حوسبة للأغراض العامة على وحدات معالجة الرسوميات Arabic GPGPU Catalan GPGPU Czech General Purpose Computation on Graphics Processing Unit German GPGPU Spanish محاسبات همه‌منظوره بر روی واحد پردازش گرافیکی Persian GPGPU Finnish General-purpose processing on graphics processing units French GPGPU HE GPGPU Italian

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).[1][2][3][4] The use of multiple video cards in one computer, or large numbers of graphics chips, further parallelizes the already parallel nature of graphics processing.[5]

Essentially, a GPGPU pipeline is a kind of parallel processing between one or more GPUs and CPUs that analyzes data as if it were in image or other graphic form. While GPUs operate at lower frequencies, they typically have many times the number of cores. Thus, GPUs can process far more pictures and graphical data per second than a traditional CPU. Migrating data into graphical form and then using the GPU to scan and analyze it can create a large speedup.

GPGPU pipelines were developed at the beginning of the 21st century for graphics processing (e.g. for better shaders). These pipelines were found to fit scientific computing needs well, and have since been developed in this direction.

The most known GPGPUs are Nvidia Tesla that are used for Nvidia DGX, alongside AMD Instinct and Intel Gaudi.

  1. ^ Fung, James; Tang, Felix; Mann, Steve (7–10 October 2002). Mediated Reality Using Computer Graphics Hardware for Computer Vision (PDF). Proceedings of the International Symposium on Wearable Computing 2002 (ISWC2002). Seattle, Washington, USA. pp. 83–89. Archived from the original (PDF) on 2 April 2012.
  2. ^ Aimone, Chris; Fung, James; Mann, Steve (2003). "An Eye Tap video-based featureless projective motion estimation assisted by gyroscopic tracking for wearable computer mediated reality". Personal and Ubiquitous Computing. 7 (5): 236–248. doi:10.1007/s00779-003-0239-6. S2CID 25168728.
  3. ^ "Computer Vision Signal Processing on Graphics Processing Units", Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2004) Archived 19 August 2011 at the Wayback Machine: Montreal, Quebec, Canada, 17–21 May 2004, pp. V-93 – V-96
  4. ^ Chitty, D. M. (2007, July). A data parallel approach to genetic programming using programmable graphics hardware Archived 8 August 2017 at the Wayback Machine. In Proceedings of the 9th annual conference on Genetic and evolutionary computation (pp. 1566-1573). ACM.
  5. ^ "Using Multiple Graphics Cards as a General Purpose Parallel Computer: Applications to Computer Vision", Proceedings of the 17th International Conference on Pattern Recognition (ICPR2004) Archived 18 July 2011 at the Wayback Machine, Cambridge, United Kingdom, 23–26 August 2004, volume 1, pages 805–808.

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