Brainstorm Optimization Hardware Implementation using FPGAs
Author(s) |
Mohammed El-Abd |
Related to |
Faculty member |
Funded |
Yes |
College |
CEAS |
Sponsor |
AUK |
Course Name |
NA |
Amount in KWD |
1000 |
Year |
2018 |
DOI |
NA |
Abstract:
Brain Storm Optimization (BSO) is a metaheuristic algorithm that has been gaining attention in solving engineering problems. The algorithm emulates the human brainstorming procedure by initializing a population and optimizing it over several generations. The algorithm enjoys intrinsic parallelism that enables the development of high-speed hardware implementations. However, investigations on accelerating the BSO are yet limited in literature. In this paper, we present a parallel BSO processor under Field Programmable Gate Arrays (FPGAs). The development includes sequentially modeling the algorithm, deriving parallel versions, targeting a rich set of benchmark evaluation functions, and performing thorough validations. The results confirm the achievement of appealing performance characteristics that significantly outperform software implementations in terms of execution speed. The paper includes thorough analysis, evaluation, and sets the ground for future works.
Citation:
Ahmed Hassanein, Mohammed El-Abd, Issam Damaj, Haseeb Ur Rehman, Parallel hardware implementation of the brain storm optimization algorithm using FPGAs, Microprocessors and Microsystems, Volume 74, 2020, 103005, ISSN 0141-9331.
Published Paper:
https://www.sciencedirect.com/science/article/abs/pii/S0141933119303448