| Title | A Performance Study of Parallel Programming via CPU and GPU on Swarm Intelligence Based Evolutionary Algorithm |
| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | Lin, Frank Po-Chen, Phoa, Frederick Kin Hing |
| Conference Name | Proceedings of the 2017 International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-4798-3 |
| Keywords | composability, CUDA, OpenMP, parallel computing, pubcrawl, swarm intelligence |
| Abstract | Algorithm parallelization diversifies a complicated computing task into small parts, and thus it receives wide attention when it is implemented to evolutionary algorithms (EA). This works considers a recently developed EA called the Swarm Intelligence Based (SIB) method as a benchmark to compare the performance of two types of parallel computing approaches: a CPU-based approach via OpenMP and a GPU-based approach via CUDA. The experiments are conducted to solve an optimization problem in the search of supersaturated designs via the SIB method. Unlike conventional suggestions, we show that the CPU-based OpenMP outperforms CUDA at the execution time. At the end of this paper, we provide several potential problems in GPU parallel computing towards EA and suggest to use CPU-based OpenMP for parallel computing of EA. |
| URL | http://doi.acm.org/10.1145/3059336.3059339 |
| DOI | 10.1145/3059336.3059339 |
| Citation Key | lin_performance_2017 |
A Performance Study of Parallel Programming via CPU and GPU on Swarm Intelligence Based Evolutionary Algorithm