GPU Programming in MATLAB

__GPU programming in MATLAB__ is intended for scientists, engineers, or students who develop or maintain applications in MATLAB and would like to accelerate their codes using GPU programming without losing the many benefits of MATLAB. The book starts with coverage of the Parallel Computing Toolbox and other MATLAB toolboxes for GPU computing, which allow applications to be ported straightforwardly onto GPUs without extensive knowledge of GPU programming. The next part covers built-in, GPU-enabled features of MATLAB, including options to leverage GPUs across multicore or different computer systems. Finally, advanced material includes CUDA code in MATLAB and optimizing existing GPU applications. Throughout the book, examples and source codes illustrate every concept so that readers can immediately apply them to their own development. * Provides in-depth, comprehensive coverage of GPUs with MATLAB, including the parallel computing toolbox and built-in features for other MATLAB toolboxes * Explains how to accelerate computationally heavy applications in MATLAB without the need to re-write them in another language * Presents case studies illustrating key concepts across multiple fields * Includes source code, sample datasets, and lecture slides \*\*

GPU programming in MATLAB is intended for scientists, engineers, or students who develop or maintain applications in MATLAB and would like to accelerate their codes using GPU programming without losing the many benefits of MATLAB. The book starts with coverage of the Parallel Computing Toolbox and other MATLAB toolboxes for GPU computing, which allow applications to be ported straightforwardly onto GPUs without extensive knowledge of GPU programming. The next part covers built-in, GPU-enabled features of MATLAB, including options to leverage GPUs across multicore or different computer systems. Finally, advanced material includes CUDA code in MATLAB and optimizing existing GPU applications. Throughout the book, examples and source codes illustrate every concept so that readers can immediately apply them to their own development.

• Provides in-depth, comprehensive coverage of GPUs with MATLAB, including the parallel computing toolbox and built-in features for other MATLAB toolboxes
• Explains how to accelerate computationally heavy applications in MATLAB without the need to re-write them in another language
• Presents case studies illustrating key concepts across multiple fields
• Includes source code, sample datasets, and lecture slides

Content: Front Matter,Copyright,Dedication,About the Authors,Foreword,PrefaceEntitled to full textChapter 1 - Introduction, Pages 1-19 Chapter 2 - Getting started, Pages 21-35 Chapter 3 - Parallel Computing Toolbox, Pages 37-70 Chapter 4 - Introduction to GPU programming in MATLAB, Pages 71-107 Chapter 5 - GPU programming on MATLAB toolboxes, Pages 109-170 Chapter 6 - Multiple GPUs, Pages 171-198 Chapter 7 - Run CUDA or PTX code, Pages 199-218 Chapter 8 - MATLAB MEX functions containing CUDA code, Pages 219-240 Chapter 9 - CUDA-accelerated libraries, Pages 241-268 Chapter 10 - Profiling code and improving GPU performance, Pages 269-294 References, Pages 295-296 List of Examples, Pages 297-300 Index, Pages 301-302 Presenting case studies illustrating key concepts across multiple fields, this book is intended for those who develop or maintain applications in MATLAB and would like to accelerate their codes using GPU programming without losing the many benefits of MATLAB. -- Edited summary from book