Name
Abstract | ||
|---|---|---|
Performance modeling of GPU kernels is a significant challenge. In this paper, we develop a novel approach to performance modeling for GPUs through abstract kernel emulation along with latency/gap modeling of resources. Experimental results on all benchmarks from the Rodinia suite demonstrate good accuracy in predicting execution time on multiple GPU platforms.
|
Year | Venue | Field |
|---|---|---|
2018 | PPOPP | Kernel (linear algebra),Suite,Computer science,Latency (engineering),Parallel computing,Emulation,Execution time,Loop parallelization |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
2 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Changwan Hong | 1 | 15 | 1.96 |
| Aravind Sukumaran-Rajam | 2 | 50 | 12.03 |
| Jinsung Kim | 3 | 5 | 1.42 |
| Prashant Singh Rawat | 4 | 40 | 4.51 |
| Sriram Krishnamoorthy | 5 | 1202 | 86.68 |
| Louis-Noël Pouchet | 6 | 15 | 2.24 |
| Fabrice Rastello | 7 | 482 | 38.30 |
| Ponnuswamy Sadayappan | 8 | 170 | 14.46 |