Mesh architecture for hardware implementation of Particle Swarm Optimization
Amin Farmahini-Farahani, Majid Laali, Amir Moghimi, Sied Mehdi Fakhraie, Saeed Safari · 2007
Particle Swarm Optimization (PSO) is an evolutionary computation method which has successfully been used in many engineering optimization problems. The major obstacle limiting the use of PSO in real-time applications is its long execution time. Hardware implementation of evolutionary algorithms has been employed to alleviate the high computational cost of complex optimization problems. In this paper, we propose a parallel scalable architecture which is well-suited for hardware implementation of PSO. The architecture is composed of a number of Processing Elements (PE) performing the algorithm computations that are connected to other PEs through communication channels. PEs are arranged based on the mesh architecture which provides either scalability or performance to execute computational intensive applications. Two communication methods are proposed based on the architecture which enable the system to solve different kinds of problems.