Exploiting seeding of random number generators for efficient domain decomposition parallelization of dissipative particle dynamics

Y. Afshar; F. Schmid; A. Pishevar; S. Worley

doi:10.1016/j.cpc.2012.12.003

Exploiting seeding of random number generators for efficient domain decomposition parallelization of dissipative particle dynamics

Y. Afshar, F. Schmid, A. Pishevar, S. Worley

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

Dissipative particle dynamics (DPD) is a new promising method commonly used in coarse-grained simulations of soft matter and biomolecular systems at constant temperature. The DPD thermostat involves the evaluation of stochastic or random forces between pairs of neighboring particles in every time step. In a parallel computing environment, the transfer of these forces from node to node can be very time consuming. In this paper we describe the implementation of a seeded random number generator with three input seeds at each step which enables the complete generation of the pairwise stochastic forces in parallel DPD simulations with minimal communication between nodes.

Original language	English (US)
Pages (from-to)	1119-1128
Number of pages	10
Journal	Computer Physics Communications
Volume	184
Issue number	4
DOIs	https://doi.org/10.1016/j.cpc.2012.12.003
State	Published - Apr 2013
Externally published	Yes

Bibliographical note

Funding Information:
Y. Afshar was a recipient of a fellowship of the Graduate School Materials Science in Mainz (MAINZ) funded through the German Research Foundation in the Excellence Initiative (GSC 266). Additionally, Y. Afshar would like to thank Dr. Michael Seaton (Computational Chemistry Group, Daresbury Laboratory) for useful discussion regarding the standard method implementation.

Keywords

Dissipative particle dynamics
Domain decomposition
Parallel computing
Random number generator
Saru

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10.1016/j.cpc.2012.12.003

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abstract = "Dissipative particle dynamics (DPD) is a new promising method commonly used in coarse-grained simulations of soft matter and biomolecular systems at constant temperature. The DPD thermostat involves the evaluation of stochastic or random forces between pairs of neighboring particles in every time step. In a parallel computing environment, the transfer of these forces from node to node can be very time consuming. In this paper we describe the implementation of a seeded random number generator with three input seeds at each step which enables the complete generation of the pairwise stochastic forces in parallel DPD simulations with minimal communication between nodes.",

keywords = "Dissipative particle dynamics, Domain decomposition, Parallel computing, Random number generator, Saru",

author = "Y. Afshar and F. Schmid and A. Pishevar and S. Worley",

note = "Funding Information: Y. Afshar was a recipient of a fellowship of the Graduate School Materials Science in Mainz (MAINZ) funded through the German Research Foundation in the Excellence Initiative (GSC 266). Additionally, Y. Afshar would like to thank Dr. Michael Seaton (Computational Chemistry Group, Daresbury Laboratory) for useful discussion regarding the standard method implementation. ",

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AU - Afshar, Y.

AU - Schmid, F.

AU - Pishevar, A.

AU - Worley, S.

N1 - Funding Information: Y. Afshar was a recipient of a fellowship of the Graduate School Materials Science in Mainz (MAINZ) funded through the German Research Foundation in the Excellence Initiative (GSC 266). Additionally, Y. Afshar would like to thank Dr. Michael Seaton (Computational Chemistry Group, Daresbury Laboratory) for useful discussion regarding the standard method implementation.

PY - 2013/4

Y1 - 2013/4

N2 - Dissipative particle dynamics (DPD) is a new promising method commonly used in coarse-grained simulations of soft matter and biomolecular systems at constant temperature. The DPD thermostat involves the evaluation of stochastic or random forces between pairs of neighboring particles in every time step. In a parallel computing environment, the transfer of these forces from node to node can be very time consuming. In this paper we describe the implementation of a seeded random number generator with three input seeds at each step which enables the complete generation of the pairwise stochastic forces in parallel DPD simulations with minimal communication between nodes.

AB - Dissipative particle dynamics (DPD) is a new promising method commonly used in coarse-grained simulations of soft matter and biomolecular systems at constant temperature. The DPD thermostat involves the evaluation of stochastic or random forces between pairs of neighboring particles in every time step. In a parallel computing environment, the transfer of these forces from node to node can be very time consuming. In this paper we describe the implementation of a seeded random number generator with three input seeds at each step which enables the complete generation of the pairwise stochastic forces in parallel DPD simulations with minimal communication between nodes.

KW - Dissipative particle dynamics

KW - Domain decomposition

KW - Parallel computing

KW - Random number generator

KW - Saru

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Exploiting seeding of random number generators for efficient domain decomposition parallelization of dissipative particle dynamics

Abstract

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Keywords

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