CUDA Programming: A Developer's Guide to Parallel Computing with GPUsNewnes, 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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Сторінка 9
... stream processors. Each PowerPC board is supervised by a dual-core AMD (Advanced Micro Devices) Opteron processor, of which there are 6912 in total. The Opteron processors act as coordinators among the nodes. Roadrunner has a ...
... stream processors. Each PowerPC board is supervised by a dual-core AMD (Advanced Micro Devices) Opteron processor, of which there are 6912 in total. The Opteron processors act as coordinators among the nodes. Roadrunner has a ...
Сторінка 15
... (Stream Processors). The original 9800 GTX card has eight SMs, giving a total of 128 SPs. However, unlike the Roadrunner, each GPU board can be purchased for a few hundred USD and it doesn't take 2.35 MW to power it. Power considerations ...
... (Stream Processors). The original 9800 GTX card has eight SMs, giving a total of 128 SPs. However, unlike the Roadrunner, each GPU board can be purchased for a few hundred USD and it doesn't take 2.35 MW to power it. Power considerations ...
Сторінка 16
... is as impressive as the NVIDIA range in terms of raw computer power. However, AMD brought its stream computing technology to the marketplace a long time. 16 CHAPTER 1 A Short History of Supercomputing ALTERNATIVES TO CUDA.
... is as impressive as the NVIDIA range in terms of raw computer power. However, AMD brought its stream computing technology to the marketplace a long time. 16 CHAPTER 1 A Short History of Supercomputing ALTERNATIVES TO CUDA.
Сторінка 17
... stream technology. OpenCL and Direct compute is not something we'll cover in this book, but they deserve a mention in terms of alternatives to CUDA. CUDA is currently only officially executable on NVIDIA hardware. While NVIDIA has a ...
... stream technology. OpenCL and Direct compute is not something we'll cover in this book, but they deserve a mention in terms of alternatives to CUDA. CUDA is currently only officially executable on NVIDIA hardware. While NVIDIA has a ...
Сторінка 18
... streaming data to or from memory. Pthreads is a library that is used significantly for multithread applications on Linux. As with OpenMP, pthreads uses threads and not processes as it is designed for parallelism within a single node ...
... streaming data to or from memory. Pthreads is a library that is used significantly for multithread applications on Linux. As with OpenMP, pthreads uses threads and not processes as it is designed for parallelism within a single node ...
Зміст
Chapter 8 MultiCPU and MultiGPU Solutions | 267 |
Chapter 9 Optimizing Your Application | 305 |
Chapter 10 Libraries and SDK | 441 |
Chapter 11 Designing GPUBased Systems | 503 |
Chapter 12 Common Problems Causes and Solutions | 527 |
Index | 565 |
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CUDA Programming: A Developer's Guide to Parallel Computing with GPUs Shane Cook Обмежений попередній перегляд - 2012 |
Загальні терміни та фрази
256 threads algorithm allocate application array atomic atomic operations blockDim.x blockIdx.x bytes calculation compiler compute 2.x const int const u32 constant memory copy CUDA CALL cuda CUDA cores dataset device device_num elements example execution Fermi Figure function GB/s GeForce GTX 470:GMEM global memory GMEM hardware host memory ID:0 GeForce GTX InfiniBand instruction issue iterations Kepler kernel L1 cache latency Linux look loop malloc Memcpy memory access memory bandwidth memory fetch merge sort node num_elem num_elements num_threads number of blocks number of threads NVIDIA OpenMP operation optimization output Parallel Nsight parameter PCI-E performance pointer prefix sum problem processor radix sort reduce registers result serial shared memory SIMD simply single SP SP SP speedup stream synchronization Tesla threadIdx.x threads per block transfer typically uint4 unsigned int usage version is faster void warp write þ¼