[SIST Seminar] Random-Batch Ewald Method for High-Scalable MD simulations

ON2021-11-23TAG: ShanghaiTech UniversityCATEGORY: Lecture

Speaker:    Prof. Zhenli XuShanghai Jiao Tong University
Time:         10:00-11:00 , Nov.25
Location:   SIST 1C 101
Host:          Prof. Qifeng Liao
The development of efficient methods for long-range systems plays important role in all-atom simulations of biomolecules and drug design. We present a random-batch Ewald (RBE) method for molecular dynamics simulations of particle systems with long-range Coulomb interactions. The RBE takes advantage of the random minibatch strategy for the force calculation between particles, leading to an order N algorithm. It is based on the Ewald splitting of the Coulomb kernel and the random importance sampling is employed in the Fourier part such that the force variance can be reduced. This new simulation method avoids the use of the FFT and greatly improves the scalability of the molecular simulations. We also discuss the treatment of the short-range interactions by using random batch idea. Numerical results, including protein solution and phase-separated electrolytes, are presented to show the attractive performance of the algorithm.

Zhenli Xu is a professor in mathematics at Shanghai Jiao Tong University (SJTU). He received B.S. M.S. and Ph.D. degrees from University of Science and Technology of China, and was postdoctoral fellow at University of North Carolina at Charlotte and Humboldt fellow at University of Stuttgart. He was selected in the Program of New Century Talents in University of Chinese Ministry of Education in 2010, and National Youth Top-notch Talent Program of Central Organization Department of China in 2012. Professor Xu is in the editorial boards of journals of Advances in Applied Mathematics and Mechanics, Communications in Mathematical Sciences, and Mathematical and Computational Applications. His research fields include fast algorithms and modeling for Coulomb many-body phenomena, nanofluidic devices, molecular dynamics, and numerical PDEs, etc.