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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... memory, decodes, and then executes that instruction. A modern processor ... fetch, every cycle, an instruction (an operator) plus some data (an operand) ... fetch and write back data, which if we say is on a 1:1 ratio with instructions ...
... memory, decodes, and then executes that instruction. A modern processor ... fetch, every cycle, an instruction (an operator) plus some data (an operand) ... fetch and write back data, which if we say is on a 1:1 ratio with instructions ...
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... fetch from the second or third level (L2 or L3) cache is required, or from the main memory if no cache line has this data already. The first level cache typically runs at or near the processor clock speed, so for the execution of our ...
... fetch from the second or third level (L2 or L3) cache is required, or from the main memory if no cache line has this data already. The first level cache typically runs at or near the processor clock speed, so for the execution of our ...
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... memory space. Like many machines of its era, it was a vector-based machine ... memory is configured in three banks of red, blue, and green, rather than being ... fetch, decode, and execute the instruction stream on each loop iteration ...
... memory space. Like many machines of its era, it was a vector-based machine ... memory is configured in three banks of red, blue, and green, rather than being ... fetch, decode, and execute the instruction stream on each loop iteration ...
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... memory), fetch the needed item, and return. Neither the tradesperson nor the client knows how long (the latency) this operation will actually take. There may be congestion on the freeway and/or queues at the hardware store (other ...
... memory), fetch the needed item, and return. Neither the tradesperson nor the client knows how long (the latency) this operation will actually take. There may be congestion on the freeway and/or queues at the hardware store (other ...
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... fetches element 0. As CPUs contain multiple levels of cache, this brings the data into the device. Typically the L3 cache is shared by all cores. Thus, the memory access from the first fetch is distributed to all cores in the CPU. By ...
... fetches element 0. As CPUs contain multiple levels of cache, this brings the data into the device. Typically the L3 cache is shared by all cores. Thus, the memory access from the first fetch is distributed to all cores in the CPU. By ...
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