Library of American University of Madaba
GPU programming in MATLAB /
by Ploskas, Nikolaos,
Authors: Samaras, Nikolaos,%author. Published by : Morgan Kaufmann, an imprint of Elsevier, (Cambridge, MA : ) Physical details: xvi, 302 p. : ill. ; 25 cm. ISBN: 0128051329 Subject(s): MATLAB. | Graphics processing units %Programming. | Parallel processing (Electronic computers) Year: 2016| Item type | Location | Call Number | Status | Notes | Date Due |
|---|---|---|---|---|---|
 Book |
AUM Main Library English Collections Hall | 006.66 P729 (Browse Shelf) | Available | 20180109 |
Browsing AUM Main Library Shelves, Shelving Location: English Collections Hall Close Shelf Browser
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| 006.60151 V562Mathematics for computer graphics / | 006.60151 V562Mathematics for computer graphics / | 006.66 O635OpenGL programming guide : | 006.66 P729GPU programming in MATLAB / | 006.663 W352Perl graphics programming / | 006.663 W352Perl graphics programming / |
Includes bibliographical references and index.
Machine generated contents note: ch. 1 Introduction -- 1.1. Parallel Programming -- 1.1.1. Introduction to Parallel Computing -- 1.1.2. Classification of Parallel Computers -- 1.1.3. Parallel Computers' Memory Architectures -- 1.2. GPU Programming -- 1.3. CUDA Architecture -- 1.4. Why GPU Programming in MATLAB? When to Use GPU Programming? -- 1.5. Our Approach: Organization of the Book -- 1.6. Chapter Review -- ch. 2 Getting Started -- 2.1. Hardware Requirements -- 2.2. Software Requirements -- 2.2.1. NVIDIA CUDA Toolkit -- Windows -- Linux -- MAC OS -- 2.2.2. MATLAB -- Windows -- Linux -- MAC OS -- 2.3. Chapter Review -- ch. 3 Parallel Computing Toolbox -- 3.1. Product Description and Objectives -- 3.2. Parallel For-Loops (parfor) -- 3.3. Single Program Multiple Data (spmd) -- 3.4. Distributed and Codistributed Arrays -- 3.5. Interactive Parallel Development (pmode) -- 3.6. GPU Computing -- 3.7. Clusters and Job Scheduling -- 3.8. Chapter Review -- ch. 4 Introduction to GPU Programming in MATLAB -- 4.1. GPU Programming Features in MATLAB -- 4.2. GPU Arrays -- 4.3. Built-In MATLAB Functions for GPUs -- 4.4. Element-Wise MATLAB Code on GPUs -- 4.5. Chapter Review -- ch. 5 GPU Programming on MATLAB Toolboxes -- 5.1. Communications System Toolbox -- 5.2. Image Processing Toolbox -- 5.3. Neural Network Toolbox -- 5.4. Phased Array System Toolbox -- 5.5. Signal Processing Toolbox -- 5.6. Statistics and Machine Learning Toolbox -- 5.7. Chapter Review -- ch. 6 Multiple GPUs -- 6.1. Identify and Run Code on a Specific GPU Device -- 6.2. Examples Using Multiple GPUs -- 6.3. Chapter Review -- ch. 7 Run CUDA or PTX Code -- 7.1. Brief Introduction to CUDA C -- 7.2. Steps to Run CUDA or PTX Code on a GPU Through MATLAB -- 7.3. Example: Vector Addition -- 7.4. Example: Matrix Multiplication -- 7.5. Chapter Review -- ch. 8 MATLAB MEX Functions Containing CUDA Code -- 8.1. Brief Introduction to MATLAB MEX Files -- 8.2. Steps to Run MATLAB MEX Functions on GPU -- 8.3. Example: Vector Addition -- 8.4. Example: Matrix Multiplication -- 8.5. Chapter Review -- ch. 9 CUDA-Accelerated Libraries -- 9.1. Introduction -- 9.2. cuBLAS -- 9.3. cuFFT -- 9.4. cuRAND -- 9.5. cuSOLVER -- 9.6. cuSPARSE -- 9.7. NPP -- 9.8. Thrust -- 9.9. Chapter Review -- ch. 10 Profiling Code and Improving GPU Performance -- 10.1. MATLAB Profiling -- 10.2. CUDA Profiling -- 10.3. Best Practices for Improving GPU Performance -- 10.4. Chapter Review.
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