PSO algorithms and GPGPU technique for electromagnetic problems

Abstract

This paper studies the efficiency of the General Purpose Computation on Graphics Processing Units (GPGPU) technique for the implementation of a parallel Particle Swarm Optimization (PSO) algorithm applied for the optimization of electromagnetic field devices. Several sequential PSO algorithms are compared in order to find the optimal configuration of an electromagnetic device, the TEAM22 benchmark electromagnetic problem. The best PSO algorithm is parallelized by using a GPGPU technique using various configurations for kernels and threads per block. Details of the parallel implementations are explained. The sequential and parallel implementations are compared using as criteria the speed up and the solution quality. The most efficient approach turned to be the one with one thread per block, which was up to 4 times faster than a sequential implementation running on hardware architectures with processors much more advanced than the core processors of the GPU.

Keywords

PSO GPGPU electromagnetic field optimization TEAM22

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