CaltechAUTHORS
Published November 12, 2018 | Version public
Book Section - Chapter Metadata-only

Shift-Collapse Acceleration of Generalized Polarizable Reactive Molecular Dynamics for Machine Learning-Assisted Computational Synthesis of Layered Materials

Creators

  • 1. ROR icon University of Southern California
  • 2. ROR icon National Science and Technology Development Agency
  • 3. ROR icon California Institute of Technology
  • 4. ROR icon Argonne National Laboratory
  • 5. ROR icon Kumamoto University

Abstract

Reactive molecular dynamics is a powerful simulation method for describing chemical reactions. Here, we introduce a new generalized polarizable reactive force-field (ReaxPQ+) model to significantly improve the accuracy by accommodating the reorganization of surrounding media. The increased computation is accelerated by (1) extended Lagrangian approach to eliminate the speed-limiting charge iteration, (2) shift-collapse computation of many-body renormalized n-tuples, which provably minimizes data transfer, (3) multithreading with round-robin data privatization, and (4) data reordering to reduce computation and allow vectorization. The new code achieves (1) weak-scaling parallel efficiency of 0.989 for 131,072 cores, and (2) eight-fold reduction of time-to-solution (T2S) compared with the original code, on an Intel Knights Landing-based computer. The reduced T2S has for the first time allowed purely computational synthesis of atomically-thin transition metal dichalcogenide layers assisted by machine learning to discover a novel synthetic pathway.

Additional Information

© 2018 IEEE. This work was supported as part of the Computational Materials Sciences Program funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, under Award Number DE-SC0014607. An award of computer time was provided by the Aurora Early Science Program. This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357.

Additional details

Identifiers

Eprint ID
94893
DOI
10.1109/ScalA.2018.00009
Resolver ID
CaltechAUTHORS:20190423-124212621

Related works

Describes
10.1109/ScalA.2018.00009 (DOI)
https://sc18.supercomputing.org/proceedings/workshops/workshop_files/ws_lasalss106s2-file1.pdf (URL)

Funding

Department of Energy (DOE)
DE-SC0014607
Department of Energy (DOE)
DE-AC02-06CH11357

Dates

Created
2019-05-10
Created from EPrint's datestamp field
Updated
2021-11-16
Created from EPrint's last_modified field

Caltech Custom Metadata

Other Numbering System Name
WAG
Other Numbering System Identifier
1306