Frontiers of Data and Computing ›› 2025, Vol. 7 ›› Issue (6): 158-169.

CSTR: 32002.14.jfdc.CN10-1649/TP.2025.06.015

doi: 10.11871/jfdc.issn.2096-742X.2025.06.015

• Technology and Application • Previous Articles     Next Articles

Parallel Implementation of the Quantum Mechanics Force Field Program of Biosystem Using Tens of Millions of Cores on the New-Generation Sunway Supercomputer

GUO Jianping1(),MAO Ruichao1,ZHANG Han1,ZHANG Yong2,GAO Jun1,*()   

  1. 1. College of Informatics, Huazhong Agricultural University, Wuhan, Hubei 430070, China
    2. Qingdao Institute of Theoretical and Computational Sciences, Shandong University, Qingdao, Shandong 266237, China
  • Received:2025-02-20 Online:2025-12-20 Published:2025-12-17
  • Contact: GAO Jun E-mail:guojianping@webmail.hzau.edu.cn;gaojun@mail.hzau.edu.cn

Abstract:

[Objective] This paper aims to achieve efficient parallelization of the explicit polarization (X-Pol) model, a quantum mechanical force field method, on a new generation of domestic supercomputers. [Methods] The PyXPOL program, a Python implementation of the quantum mechanical force field method, is developed. It adopts a two-level parallel architecture of MPI+Athread. By introducing the neighbor list method, the parallel computation of non-bonded interactions is achieved. An S-shaped sorting optimization method for computational workload is employed to achieve load balancing. Considering the characteristics of the SW26010-Pro processor, the quantum chemical calculation program in the X-Pol model is optimized. [Results] The results indicate that the PyXPOL program demonstrates weak scalability on ten million cores. Compared with the calculation using 50,050 cores, the parallel efficiency of the ten-million-core calculation can reach 75%. Moreover, it also achieves large-scale parallel calculations for a biological system with 170,788 atoms. The parallel efficiency of 3 million cores compared to 50,050 cores reaches 82%. [Conclusions] The PyXPOL program achieves efficient parallelization of the X-Pol quantum mechanical force field method on the new generation of domestic supercomputers, significantly improving the computational efficiency for large-scale biological molecular systems. It provides a powerful tool for the application of quantum mechanical force field methods in large-scale parallel computing.

Key words: Explicit polarization (X-Pol) model, two-level parallel, quantum mechanical force field