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MK.Accelerating MATLAB with GPUs.A Primer with Examples.2014.pdf
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This book is aimed primarily at the graduate students and researchers in the field of
engineering, science, and technology who need huge data processing without losing
the many benefits of MATLAB. However, MATLAB users come from various backgrounds
and do not necessarily have much programming experience. For those whose
backgrounds are not from programming, GPU acceleration for MATLAB may distract
their algorithm development and introduce unnecessary hassles, even when setting the
environment. This book targets the readers who have some or a lot of experience on
MATLAB coding but not enough depth in either C coding or the computer architecture
for parallelization. So readers can focus more on their research and work by
avoiding non-algorithmic hassles in using GPU and CUDA in MATLAB.
As a primer, the book will start with the basics, walking through the process of
setting MATLAB for CUDA (in Windows and Mac OSX), creating c-mex and m-file
profiling, then guide the users through the expert-level topics such as third-party
CUDA libraries. It also provides many practical ways to modify users’ MATLAB
codes to better utilize the immense computational power of graphics processors.
This book guides the reader to dramatically maximize the MATLAB speed
using NVIDIA’s Graphics Processing Unit (GPU). NVIDIA’s Compute Unified
Device Architecture (CUDA) is a parallel computing architecture originally
designed for computer games but is getting a reputation in the general science and
technology fields for its efficient massive computation power. From this book, the
reader can take advantage of the parallel processing power of GPU and abundant
CUDA scientific libraries for accelerating MATLAB code with no or less effort
and time, and bring readers’ researches and works to a higher level
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