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GPU computation; massive parallel processing; CUDA; system identification
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).
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