Name
Abstract | ||
|---|---|---|
Sunway TaihuLight system is the first supercomputer offering a peak performance over 100 PFlops, which can be utilized to parallelize Non-dominated Sorting Genetic Algorithm II (NSGA-II), a standard approach to multi-objective optimization. However, insufficient off-chip memory bandwidth and limited scratchpad memory capacity of the supercomputer hinder the performance improvement of parallellizing NSGA-II. In this article, we propose an optimized parallel NSGA-II on Sunway TaihuLight system, called swNSGA-II, by utilizing process- and thread-level parallelism of the system based on an improved island/master-slave model. To overcome the hurdles of low memory bandwidth and capacity, we propose a data sharing scheme based on register-level communication that can efficiently parallelize non-dominated sorting and crowding-distance computation of NSGA-II. Several optimization techniques including vectorization, direct memory accessing, and double buffering are also adopted to further accelerate swNSGA-II. Experiment results show that the proposed swNSGA-II can achieve a speedup of 41284 on a use case of path planning, and a speedup of 62692 on ZDT1 as compared to conventional NSGA-II. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TPDS.2020.3037082 | IEEE Transactions on Parallel and Distributed Systems |
Keywords | DocType | Volume |
Sunway TaihuLight,many-core processor,NSGA-II,multi-objective optimization | Journal | 32 |
Issue | ISSN | Citations |
4 | 1045-9219 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |