Graphics card as a cheap supercomputer

Přikryl, Jan. "Graphics card as a cheap supercomputer." Programs and Algorithms of Numerical Mathematics. Prague: Institute of Mathematics AS CR, 2013. 162-167. <http://eudml.org/doc/271357>.

@inProceedings{Přikryl2013,
abstract = {The current powerful graphics cards, providing stunning real-time visual effects for computer-based entertainment, have to accommodate powerful hardware components that are able to deliver the photo-realistic simulation to the end-user. Given the vast computing power of the graphics hardware, its producers very often offer a programming interface that makes it possible to use the computational resources of the graphics processors (GPU) to more general purposes. This step gave birth to the so-called GPGPU (general-purpose GPU) processors that – if programmed correctly – are able to achieve astonishing performance in floating point operations. In this paper we will briefly overview nVidia CUDA technology and we will demonstrate a process of developing a simple GPGPU application both in the native GPGPU style and in the add-ons for Matlab (Jacket and Parallel Toolbox).},
author = {Přikryl, Jan},
booktitle = {Programs and Algorithms of Numerical Mathematics},
keywords = {GPU computation; massive parallel processing; CUDA; system identification},
location = {Prague},
pages = {162-167},
publisher = {Institute of Mathematics AS CR},
title = {Graphics card as a cheap supercomputer},
url = {http://eudml.org/doc/271357},
year = {2013},
}

TY - CLSWK
AU - Přikryl, Jan
TI - Graphics card as a cheap supercomputer
T2 - Programs and Algorithms of Numerical Mathematics
PY - 2013
CY - Prague
PB - Institute of Mathematics AS CR
SP - 162
EP - 167
AB - The current powerful graphics cards, providing stunning real-time visual effects for computer-based entertainment, have to accommodate powerful hardware components that are able to deliver the photo-realistic simulation to the end-user. Given the vast computing power of the graphics hardware, its producers very often offer a programming interface that makes it possible to use the computational resources of the graphics processors (GPU) to more general purposes. This step gave birth to the so-called GPGPU (general-purpose GPU) processors that – if programmed correctly – are able to achieve astonishing performance in floating point operations. In this paper we will briefly overview nVidia CUDA technology and we will demonstrate a process of developing a simple GPGPU application both in the native GPGPU style and in the add-ons for Matlab (Jacket and Parallel Toolbox).
KW - GPU computation; massive parallel processing; CUDA; system identification
UR - http://eudml.org/doc/271357
ER -