CUDA Programming: A Developer's Guide to Parallel Computing with GPUs
Newnes, 28 груд. 2012 р. - 600 стор.
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.
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Understanding the different memory types and how they are used within CUDA is the single largest factor influencing performance. Here we take a detailed explanation, with examples, of how the various memory types work and the pitfalls ...
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There is a big problem with this approachdit requires programmers to switch from their traditional serial, single-thread approach, to dealing with multiple threads all executing at once. Now the programmer has to think about two, four, ...
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Chapter 8 MultiCPU and MultiGPU Solutions
Chapter 9 Optimizing Your Application
Chapter 10 Libraries and SDK
Chapter 11 Designing GPUBased Systems
Chapter 12 Common Problems Causes and Solutions