CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs

CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs
  • Paperback: 600 pages
  • Publisher: WOW! eBook; 1st edition (November 27, 2012)
  • Language: English
  • ISBN-10: 0124159338
  • ISBN-13: 978-0124159334
eBook Description:

CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs

  • 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

CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs

If you need to learn CUDA but don’t have experience with parallel computing, CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs 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.

If you need to learn CUDA but don’t have experience with parallel computing, CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs 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.

From the Back Cover

If you need to learn CUDA but don’t have experience with parallel computing, CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs 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

If you need to learn CUDA but don’t have experience with parallel computing, CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs 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.

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