Compute Unified Device Architecture Application Suitability
Graphics processing units (GPUs) can provide excellent speedups on some, but not all, general-purpose workloads. Using a set of computational GPU kernels as examples, the authors show how to adapt kernels to utilize the architectural features of a GeForce 8800 GPU and what finally limits the achieva...
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| Veröffentlicht in: | Computing in science & engineering 2009-05, Vol.11 (3), p.16-26 |
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| container_title | Computing in science & engineering |
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| creator | Hwu, Wen-Mei Rodrigues, Christopher Ryoo, Shane Stratton, John |
| description | Graphics processing units (GPUs) can provide excellent speedups on some, but not all, general-purpose workloads. Using a set of computational GPU kernels as examples, the authors show how to adapt kernels to utilize the architectural features of a GeForce 8800 GPU and what finally limits the achievable performance. |
| doi_str_mv | 10.1109/MCSE.2009.48 |
| format | Article |
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| ispartof | Computing in science & engineering, 2009-05, Vol.11 (3), p.16-26 |
| issn | 1521-9615 1558-366X |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Architecture benchmarks Central Processing Unit Computation compute unified device architecture Computer architecture Costs CUDA Devices general-purpose computing on GPU GPGPU Graphics Hardware Kernel Kernels Multicore processing Parallel processing Phased arrays software optimization Workload |
| title | Compute Unified Device Architecture Application Suitability |
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