A hybrid parallel architecture for electrostatic interactions in the simulation of dissipative particle dynamics

Published: 4 August 2017| Version 1 | DOI: 10.17632/zncf24fhpv.1
Shengchun Yang,
Zhong-Yuan Lu,
Hu-Jun Qian,
Yong-Lei Wang,
Jie-Ping Han


In this work, we upgraded the electrostatic interaction method of CU-ENUF (S.-C. Yang, Y.-L. Wang, et al., J. Comput. Chem. 37, 2016, 378–387) which first applied CUNFFT (nonequispaced Fourier transforms based on CUDA) to the reciprocal-space electrostatic computation and made the computation of electrostatic interaction done thoroughly in GPU. The upgraded edition of CU-ENUF runs concurrently in a hybrid parallel way that enables the computation parallelizing on multiple computer nodes firstly, then further on the installed GPU in each computer. By this parallel strategy, the size of simulation system will be never restricted to the throughput of a single CPU or GPU. The most critical technical problem is how to parallelize a CUNFFT in the parallel strategy, which is conquered effectively by deep-seated research of basic principles and some algorithm skills. Furthermore, the upgraded method is capable of computing electrostatic interactions for both the atomistic molecular dynamics (MD) and the dissipative particle dynamics (DPD). Finally, the benchmarks conducted for validation and performance indicate that the upgraded method is able to not only present a good precision when setting suitable parameters, but also give an efficient way to compute electrostatic interactions for huge simulation systems.



Computational Physics, Parallel Computing, Molecular Dynamics, Electrostatic Interactions