Parallel genetic algorithm for synthesis of optimal circulant networks on Kunpeng processors
Oleg G. Monakhov, Emilia A. Monakhova · 2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON) · 2022
Parallel versions of the genetic algorithm based on the MPI model are implemented to optimize circulant networks, which are of practical interest in the design of systems on a chip and supercomputer systems. The problem of finding the optimal circulant networks with minimal average distance for the given number of nodes and given degree is investigated. An analysis of the effectiveness of parallel programs for synthesis of optimal circulant networks with different numbers of MPI processes on a cluster of Kunpeng processors was carried out. The speedup of parallel computing schemes on several cores and nodes were experimentally evaluated and analyzed. The results of the synthesis of optimal circulant networks of various degrees of nodes with a minimum average distance are presented. The proposed parallel genetic algorithm allows to obtain optimal circulants with a minimum average distance and better bisection width for the known circulant networks with large number of nodes and degrees.