Improving the Performance of Whale Optimization Algorithm through OpenCL-Based FPGA Accelerator
Joint Authors
Zhou, Xianyu
Yang, Dongsheng
Yang, Zhile
Jiang, Qiangqiang
Guo, Yuanjun
Wang, Zheng
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-16
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Whale optimization algorithm (WOA), known as a novel nature-inspired swarm optimization algorithm, demonstrates superiority in handling global continuous optimization problems.
However, its performance deteriorates when applied to large-scale complex problems due to rapidly increasing execution time required for huge computational tasks.
Based on interactions within the population, WOA is naturally amenable to parallelism, prompting an effective approach to mitigate the drawbacks of sequential WOA.
In this paper, field programmable gate array (FPGA) is used as an accelerator, of which the high-level synthesis utilizes open computing language (OpenCL) as a general programming paradigm for heterogeneous System-on-Chip.
With above platform, a novel parallel framework of WOA named PWOA is presented.
The proposed framework comprises two feasible parallel models called partial parallel and all-FPGA parallel, respectively.
Experiments are conducted by performing WOA on CPU and PWOA on OpenCL-based FPGA heterogeneous platform, to solve ten well-known benchmark functions.
Meanwhile, other two classic algorithms including particle swarm optimization (PSO) and competitive swarm optimizer (CSO) are adopted for comparison.
Numerical results show that the proposed approach achieves a promising computational performance coupled with efficient optimization on relatively large-scale complex problems.
American Psychological Association (APA)
Jiang, Qiangqiang& Guo, Yuanjun& Yang, Zhile& Wang, Zheng& Yang, Dongsheng& Zhou, Xianyu. 2020. Improving the Performance of Whale Optimization Algorithm through OpenCL-Based FPGA Accelerator. Complexity،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1144568
Modern Language Association (MLA)
Jiang, Qiangqiang…[et al.]. Improving the Performance of Whale Optimization Algorithm through OpenCL-Based FPGA Accelerator. Complexity No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1144568
American Medical Association (AMA)
Jiang, Qiangqiang& Guo, Yuanjun& Yang, Zhile& Wang, Zheng& Yang, Dongsheng& Zhou, Xianyu. Improving the Performance of Whale Optimization Algorithm through OpenCL-Based FPGA Accelerator. Complexity. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1144568
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1144568