Name
Abstract | ||
|---|---|---|
Auto-tuning has become increasingly popular for optimizing non-functional parameters of parallel programs. The typically large search space requires sophisticated techniques to find well performing parameter values in a reasonable amount of time. Different parts of a program often perform best with different parameter values. We therefore subdivide programs into several regions, and try to optimize the parameter values for each of those regions separately as opposed to setting the parameter values globally for the entire program. As this enlarges the search space even further, we have to extend existing auto-tuning techniques in order to obtain good results. In this paper we introduce a novel enhancement to the RS-GDE3 algorithm which is used to explore the search space for auto-tuning programs with multiple regions regarding several objectives. We have implemented our auto-tuner using the Insieme compiler and runtime system. In comparison to a non-optimized parallel version of the tested programs, our novel approach achieves up to 7.6, 10.5, and 61.6 fold improvements for three tuned objectives wall time, energy consumption, and resource usage, respectively. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ICPPW.2017.37 | 2017 46th International Conference on Parallel Processing Workshops (ICPPW) |
Keywords | Field | DocType |
auto-tuning,code regions,multi-objective,OpenMP,parallel programs,energy | Computer science,Instruction set,Parallel computing,Compiler,Energy consumption,Tuner,Distributed computing,Runtime system | Conference |
ISSN | ISBN | Citations |
1530-2016 | 978-1-5386-1045-9 | 1 |
PageRank | References | Authors |
0.35 | 23 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Klaus Kofler | 1 | 139 | 12.29 |
| Juan José Durillo | 2 | 272 | 14.31 |
| Philipp Gschwandtner | 3 | 58 | 7.15 |
| Thomas Fahringer | 4 | 2847 | 254.09 |