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 68
... num_threads>>>(param1, param2,.); For error checking of kernels, we'll use the following function: __host__ void cuda_error_check(const char * prefix, const char * postfix) { if (cudaPeekAtLastError() !1⁄4 cudaSuccess) { printf("\n%s%s ...
... num_threads>>>(param1, param2,.); For error checking of kernels, we'll use the following function: __host__ void cuda_error_check(const char * prefix, const char * postfix) { if (cudaPeekAtLastError() !1⁄4 cudaSuccess) { printf("\n%s%s ...
Сторінка 77
... num_threads>>>(param1, param2, .) There are some other parameters you can pass, and we'll come back to this, but for now you have two important parameters to look at: num_blocks and num_threads. These can be either variables or literal ...
... num_threads>>>(param1, param2, .) There are some other parameters you can pass, and we'll come back to this, but for now you have two important parameters to look at: num_blocks and num_threads. These can be either variables or literal ...
Сторінка 78
... num_threads>>>(param1, param2,...) If you change this from one to two, you double the number of threads you are asking the GPU to invoke on the hardware. Thus, the same call, some_kernel_func<<< 2, 128 >>>(a, b, c); will call the GPU ...
... num_threads>>>(param1, param2,...) If you change this from one to two, you double the number of threads you are asking the GPU to invoke on the hardware. Thus, the same call, some_kernel_func<<< 2, 128 >>>(a, b, c); will call the GPU ...
Сторінка 81
... num_threads = 64; Char Ch; /* Declare pointers for GPU based params k / unsigned int * gpu_block; unsigned int * gpu_thread; unsigned int * gpu_Warp; unsigned int * gpu_cal c_thread; /* Declare loop counter for use later */ unsigned int ...
... num_threads = 64; Char Ch; /* Declare pointers for GPU based params k / unsigned int * gpu_block; unsigned int * gpu_thread; unsigned int * gpu_Warp; unsigned int * gpu_cal c_thread; /* Declare loop counter for use later */ unsigned int ...
Сторінка 154
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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