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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507 ECC memory support..................................................................................... 508 Tesla compute cluster driver (TCC).
... making a DVD from your home movies (video transcoding)dwe see most mainstream video packages now supporting CUDA. The average speedup is 5 to 10 times in this domain. Along with the introduction of CUDA came the Tesla series.
Along with the introduction of CUDA came the Tesla series of cards. These cards are not graphics cards, and in fact they have no DVI or VGA connectors on them. They are dedicated compute cards aimed at scientific computing.
... 195 690 GK104 3072 4GB 5620 2 x 192 300 Tesla C870 G80 128 1.5GB 518 77 171 Tesla C1060 G200 240 4GB 933 102 188 Tesla C2070 GF100 448 6GB 1288 144 247 Tesla K10 GK104 3072 8GB 5184 2 x 160 250 The great thing about CUDA is that, ...
Compute level 1.0 is found on the older graphics cards, for example, the original 8800 Ultras and many of the 8000 series cards as well as the Tesla C/D/S870s. The main features lacking in compute 1.0 cards are those for atomic ...
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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