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

By: Material type: TextTextSeries: Publication details: Amsterdam : Morgan Kaufmann , c2013.Description: xiv, 576 p. : ill. ; 24 cmISBN:
  • 978-9351071785
Subject(s): 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 kitPractical 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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Item type Current library Call number Status Date due Barcode
REGULAR University of Wollongong in Dubai Main Collection 005.275 CO CU (Browse shelf(Opens below)) Available T0012794

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 kitPractical 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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