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Title: Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

Abstract

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scaling laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.

Authors:
 [1];  [2];  [1];  [1]
  1. Max Planck Inst. for Polymer Research, Mainz (Germany)
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE; German Research Foundation (DFG)
OSTI Identifier:
1412879
Report Number(s):
LA-UR-17-30265
Journal ID: ISSN 2470-0045; TRN: US1800388
Grant/Contract Number:  
AC52-06NA25396
Resource Type:
Accepted Manuscript
Journal Name:
Physical Review E
Additional Journal Information:
Journal Volume: 96; Journal Issue: 5; Journal ID: ISSN 2470-0045
Publisher:
American Physical Society (APS)
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; 97 MATHEMATICS AND COMPUTING; Atomic and Nuclear Physics

Citation Formats

Guzman, Horacio V., Junghans, Christoph, Kremer, Kurt, and Stuehn, Torsten. Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes. United States: N. p., 2017. Web. doi:10.1103/PhysRevE.96.053311.
Guzman, Horacio V., Junghans, Christoph, Kremer, Kurt, & Stuehn, Torsten. Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes. United States. doi:10.1103/PhysRevE.96.053311.
Guzman, Horacio V., Junghans, Christoph, Kremer, Kurt, and Stuehn, Torsten. Mon . "Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes". United States. doi:10.1103/PhysRevE.96.053311. https://www.osti.gov/servlets/purl/1412879.
@article{osti_1412879,
title = {Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes},
author = {Guzman, Horacio V. and Junghans, Christoph and Kremer, Kurt and Stuehn, Torsten},
abstractNote = {Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scaling laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.},
doi = {10.1103/PhysRevE.96.053311},
journal = {Physical Review E},
number = 5,
volume = 96,
place = {United States},
year = {2017},
month = {11}
}

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Cited by: 4 works
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