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Large-Scale Molecular Dynamics Simulation Based on Heterogeneous Many-Core Architecture.
Zhou, Xu; Wei, Zhiqiang; Lu, Hao; He, Jiaqi; Gao, Yuan; Hu, Xiaotong; Wang, Cunji; Dong, Yujie; Liu, Hao.
Afiliación
  • Zhou X; College of Computer Science and Technology, Ocean University of China, Qingdao 266100, China.
  • Wei Z; College of Computer Science and Technology, Ocean University of China, Qingdao 266100, China.
  • Lu H; College of Computer Science and Technology, Ocean University of China, Qingdao 266100, China.
  • He J; College of Computer Science and Technology, Ocean University of China, Qingdao 266100, China.
  • Gao Y; College of Computer Science and Technology, Ocean University of China, Qingdao 266100, China.
  • Hu X; College of Computer Science and Technology, Ocean University of China, Qingdao 266100, China.
  • Wang C; College of Computer Science and Technology, Ocean University of China, Qingdao 266100, China.
  • Dong Y; College of Computer Science and Technology, Ocean University of China, Qingdao 266100, China.
  • Liu H; College of Computer Science and Technology, Ocean University of China, Qingdao 266100, China.
J Chem Inf Model ; 64(3): 851-861, 2024 02 12.
Article en En | MEDLINE | ID: mdl-38299978
ABSTRACT
As the application of molecular dynamics (MD) simulations continues to evolve, the demand for accelerating large-scale simulation systems and handling of enormous simulation tasks is steadily increasing. We propose a parallel acceleration method for large-scale MD simulations based on Sunway heterogeneous many-core processors. This method integrates task scheduling, simulation calculations, and data storage, effectively tackling issues related to large-scale simulations and numerous simulation tasks. The task scheduling strategy flexibly handles tasks on various scales and enables parallel execution of multiple tasks. During the simulation calculations, we ported GROMACS to the Sunway architecture and accelerated the calculation of short-range forces through a heterogeneous processor. Our method achieves approximately 10-fold acceleration and 90% scalability when executing a single simulation task. When handling numerous simulation tasks, our method achieves parallel execution of all of the tasks with 90% scalability. By employing our method, we carried out 50 ns simulations on over 3000 distinct conotoxin structures individually within just 5 h. Additionally, we evaluated more than 200 protein-ligand complexes, and the simulation efficiency significantly exceeded that of midsized to small GPU clusters.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Simulación de Dinámica Molecular Idioma: En Revista: J Chem Inf Model Asunto de la revista: INFORMATICA MEDICA / QUIMICA Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Simulación de Dinámica Molecular Idioma: En Revista: J Chem Inf Model Asunto de la revista: INFORMATICA MEDICA / QUIMICA Año: 2024 Tipo del documento: Article País de afiliación: China