Parallel Mass Transfer Simulation of Nanoparticles Using Nonblocking Communications

Abstract

This paper presents experiences and results obtained in optimizing parallelization of the mass transfer simulation in the High Gradient Magnetic Separation (HGMS) of nanoparticles using nonblocking communication techniques in the point-to-point and collective model. We study the dynamics of mass transfer statistically in terms of particle volume concentration and the continuity equation, which is solved numerically by using the finite-difference method to compute concentration distribution in the simulation domain at a given time. In the parallel simulation, total concentration data in the simulation domain are divided row-wise and distributed equally to a group of processes. We propose two parallel algorithms based on the row-wise partitioning: algorithms with nonblocking send/receive and nonblocking scatter/gather using the NBC library. We compare the performance of both versions by measuring their parallel speedup and efficiency. We also investigate the communication overhead in both versions. Our results show that the nonblocking collective communication can improve the performance of the simulation when the number of processes is large.