General-Purpose Computing on Graphics Processing Units
A General-Purpose Computing on Graphics Processing Units is a Graphics Processing Unit that ...
- See: Central Processing Unit, Video Card, Scientific Computing, Graphics Processing Unit, Computer Graphics, Graphics Pipeline, Parallel Computing, Multi-Core Processor, Speedup.
References
2017
- (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/General-purpose_computing_on_graphics_processing_units Retrieved:2017-9-9.
- General-purpose computing on graphics processing units (GPGPU, rarely 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] The use of multiple video cards in one computer, or large numbers of graphics chips, further parallelizes the already parallel nature of graphics processing. [4] In addition, even a single GPU-CPU framework provides advantages that multiple CPUs on their own do not offer due to the specialization in each chip.
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 operate on pictures and graphical data effectively far faster than a traditional CPU. Migrating data into graphical form and then using the GPU to scan and analyze it can result in profound speedup.
GPGPU pipelines were first developed for better, more general 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.
- General-purpose computing on graphics processing units (GPGPU, rarely 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] The use of multiple video cards in one computer, or large numbers of graphics chips, further parallelizes the already parallel nature of graphics processing. [4] In addition, even a single GPU-CPU framework provides advantages that multiple CPUs on their own do not offer due to the specialization in each chip.
- ↑ Fung, et al., "Mediated Reality Using Computer Graphics Hardware for Computer Vision", Proceedings of the International Symposium on Wearable Computing 2002 (ISWC2002), Seattle, Washington, USA, 7–10 October 2002, pp. 83–89.
- ↑ An EyeTap video-based featureless projective motion estimation assisted by gyroscopic tracking for wearable computer mediated reality, ACM Personal and Ubiquitous Computing published by Springer Verlag, Vol.7, Iss. 3, 2003.
- ↑ "Computer Vision Signal Processing on Graphics Processing Units", Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2004): Montreal, Quebec, Canada, 17–21 May 2004, pp. V-93 – V-96
- ↑ "Using Multiple Graphics Cards as a General Purpose Parallel Computer: Applications to Computer Vision", Proceedings of the 17th International Conference on Pattern Recognition (ICPR2004), Cambridge, United Kingdom, 23–26 August 2004, volume 1, pages 805–808.