Name
Abstract | ||
|---|---|---|
This paper proposes a parallel scheme for accelerating parameter sweep applications on a graphics processing unit. By using hundreds of cores on the graphics processing unit, we found that our scheme simultaneously processes multiple parameters rather than a single parameter. The simultaneous sweeps exploit the similarity of computing behaviors shared by different parameters, thus allowing memory accesses to be coalesced into a single access if similar irregularities appear among the parameters' computational tasks. In addition, our scheme reduces the amount of off-chip memory access by unifying the data that are commonly referenced by multiple parameters and by placing the unified data in the fast on-chip memory. In several experiments, we applied our scheme to practical applications and found that our scheme can perform up to 8.5times faster than a naive scheme that processes a single parameter at a time. We also include a discussion on application characteristics that are required for our scheme to outperform the naive scheme. Copyright (c) 2013 John Wiley & Sons, Ltd. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1002/cpe.3016 | CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE |
Keywords | DocType | Volume |
parameter sweep,acceleration,GPU,CUDA | Journal | 26 |
Issue | ISSN | Citations |
2 | 1532-0626 | 1 |
PageRank | References | Authors |
0.35 | 18 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fumihiko Ino | 1 | 317 | 38.63 |
| Kentaro Shigeoka | 2 | 3 | 1.07 |
| Tomohiro Okuyama | 3 | 16 | 2.23 |
| Masaya Motokubota | 4 | 1 | 0.69 |
| Kenichi Hagihara | 5 | 528 | 56.94 |