Name
Title | ||
|---|---|---|
Efficient Performance Estimation and Work-Group Size Pruning for OpenCL Kernels on GPUs. |
Abstract | ||
|---|---|---|
Graphic Processing Units (GPUs) play a vital role in state-of-the-art high-performance scientific computing realm and research work towards its performance analysis is crucial but nontrivial. Extant GPU performance models are far from practical use, while fine-grained GPU simulation requires a considerably large time cost. Moreover, massive amounts of designs with various program inputs and parame... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TPDS.2019.2958343 | IEEE Transactions on Parallel and Distributed Systems |
Keywords | Field | DocType |
Kernel,Graphics processing units,Measurement,Runtime,Estimation,Hardware,Analytical models | Design space,Kernel (linear algebra),Pipeline transport,Computer science,Source code,Parallel computing,Performance estimation,Extant taxon,Distributed computing,Pruning | Journal |
Volume | Issue | ISSN |
31 | 5 | 1045-9219 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiebing Wang | 1 | 6 | 2.50 |
| Xuehai Qian | 2 | 320 | 27.71 |
| Alois Knoll Knoll | 3 | 1700 | 271.32 |
| Kai Huang | 4 | 468 | 45.69 |