GPU Programming in MATLAB

Häftad, Engelska, 2016

572 kr

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Beskrivning

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

Produktinformation

Utgivningsdatum:2016-07-28
Mått:191 x 235 x 21 mm
Vikt:680 g
Format:Häftad
Språk:Engelska
Antal sidor:318
Förlag:Elsevier Science
ISBN:9780128051320

Utforska kategorier

Programmeringsböcker inom Data och IT

Mer om författaren

Nikolaos Ploskas is a Postdoctoral Researcher at the Department of Chemical Engineering, Carnegie Mellon University, USA. He received his Bachelor of Science degree, Master’s degree, and Ph.D. in Computer Systems from the Department of Applied Informatics of the University of Macedonia, Greece. His primary researchinterests are in:Operations research,Mathematical programming,Linear programming,Parallel programming,GPU programming,Decision support systems.Dr. Ploskas has participated in several international and national research projects. He is the author or co-author of writings in more than 40 publications, including high-impact journals and book chapters, and conference publications. He has also served as a reviewer for many scientific journals. He received an honorary award from HELORS (Hellenic Operations Research Society) for the best doctoral dissertation in operations research (2014). Nikolaos Samaras is a Professor at the Department of Applied Informatics, School of Information Sciences, University of Macedonia, Greece. Professor Samaras’s current-research interests are at the interface between computer science and operations research, which apply to a variety of engineering and scientific systems: Linear/Non Linear optimization: theory, algorithms, and software Network optimization: theory, algorithms, and software Scientific computing: HPC, and GPU-programming He has served on the editorial board of the Operations Research: An International Journal, and as a reviewer in many scientific journals. He has also held numerous positions within HELORS (Hellenic Operations Research Society). He was awarded with the Thomson ISI/ASIS&T Citation Analysis Research Grant (2005). Dr. Samaras has published more than 35 journal papers in high-impact journals, including Computational Optimization and Applications, Computers and Operations Research, European Journal of Operational Research, Annals of Operations Research, Journal of Artificial Intelligence Research, Discrete Optimization, Applied Mathematics and Computation, International Journal of Computer Mathematics, Electronics Letters, Computer Applications in Engineering Education, Journal of Computational Science, and Applied Thermal Engineering. He has also published more than 85 conference papers.

Recensioner i media

"With GPU programming becoming commonplace, such a dedicated, detailed and highly readable book on this subject is a welcome addition. This textbook should be on the bookshelf of any MATLAB programmer who plans to employ GPU parallelization." --Yair Altman, author: Accelerating MATLAB Performance (CRC Press, 2014), http://UndocumentedMatlab.com

Innehållsförteckning

1. Introduction2. Getting started3. Parallel Computing Toolbox4. Introduction to GPU programming in MATLAB5. GPU programming on MATLAB toolboxes6. Multiple GPUs7. Run CUDA or PTX code8. MATLAB MEX functions containing CUDA code9. CUDA-accelerated libraries10. Profiling code and improving GPU performance