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CUDA programming : a developer's guide to parallel computing with GPUs / Shane Cook.

By: Cook, Shane
Material type: TextTextPublisher: Amsterdam ; Boston : Elsevier, MK, c2013Edition: 1stDescription: xiv, 576 p. : ill. ; 24 cmISBN: 9780124159334; 0124159338Subject(s): Application software -- Development | Parallel programming (Computer science) | Computer architecture | Parallel processing (Electronic computers)DDC classification: 005.275 LOC classification: QA76.76.A65 | C668 2013Online resources: Publisher description Summary: "If you need to learn CUDA but don't have experience with parallel computing, CUDA Programming: A Developer's Introduction offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation. Chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. Later, the book demonstrates CUDA in practice for optimizing applications, adjusting to new hardware, and solving common problems. Comprehensive introduction to parallel programming with CUDA, for readers new to both. Detailed instructions help readers optimize the CUDA software development kit. Practical techniques illustrate working with memory, threads, algorithms, resources, and more. Covers CUDA on multiple hardware platforms: Mac, Linux and Windows with several NVIDIA chipsets. Each chapter includes exercises to test reader knowledge." --
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005.275 C.S.C 2013 (Browse shelf) Available 22042

Includes bibliographical references and index.

"If you need to learn CUDA but don't have experience with parallel computing, CUDA Programming: A Developer's Introduction offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA installation. Chapters on core concepts including threads, blocks, grids, and memory focus on both parallel and CUDA-specific issues. Later, the book demonstrates CUDA in practice for optimizing applications, adjusting to new hardware, and solving common problems. Comprehensive introduction to parallel programming with CUDA, for readers new to both. Detailed instructions help readers optimize the CUDA software development kit. Practical techniques illustrate working with memory, threads, algorithms, resources, and more. Covers CUDA on multiple hardware platforms: Mac, Linux and Windows with several NVIDIA chipsets. Each chapter includes exercises to test reader knowledge." --

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