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文件名称:MATLAB-CUDA
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- 上传时间：2012-11-16
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The latest generation of high-end video cards off er considerable
computing power using their 100–200 on-card processors, 0.3–1.0+ GB
of RAM, and fast inter-processor communications. One promising
application of this Graphics Processing Unit (GPU) computing
capability is through Matlab and Matlab mex functions. With a properly developed mex function, the user-friendly Matlab interface can be used to perform behind-the-scenes parallel computations on the GPU. -The latest generation of high-end video cards offer considerable computing power using their 100-200 on-card processors, 0.3-1.0+ GB of RAM, and fast inter-processor communications. One promising application of this Graphics Processing Unit (GPU) computing capability is through Matlab and Matlab mex functions. With a properly developed mex function, the user-friendly Matlab interface can be used to perform behind-the-scenes parallel computations on the GPU.
computing power using their 100–200 on-card processors, 0.3–1.0+ GB
of RAM, and fast inter-processor communications. One promising
application of this Graphics Processing Unit (GPU) computing
capability is through Matlab and Matlab mex functions. With a properly developed mex function, the user-friendly Matlab interface can be used to perform behind-the-scenes parallel computations on the GPU. -The latest generation of high-end video cards offer considerable computing power using their 100-200 on-card processors, 0.3-1.0+ GB of RAM, and fast inter-processor communications. One promising application of this Graphics Processing Unit (GPU) computing capability is through Matlab and Matlab mex functions. With a properly developed mex function, the user-friendly Matlab interface can be used to perform behind-the-scenes parallel computations on the GPU.
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MATLAB CUDA.pdf
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