RPYFMM: Parallel adaptive fast multipole method for Rotne–Prager–Yamakawa tensor in biomolecular hydrodynamics simulations

W. Guan; X. Cheng; J. Huang; G. Huber; W. Li; J. A. McCammon; B. Zhang

doi:10.1016/j.cpc.2018.02.005

RPYFMM: Parallel adaptive fast multipole method for Rotne–Prager–Yamakawa tensor in biomolecular hydrodynamics simulations

W. Guan, X. Cheng, J. Huang, G. Huber, W. Li, J. A. McCammon, B. Zhang

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

7 Scopus citations

Abstract

RPYFMM is a software package for the efficient evaluation of the potential field governed by the Rotne–Prager–Yamakawa (RPY) tensor interactions in biomolecular hydrodynamics simulations. In our algorithm, the RPY tensor is decomposed as a linear combination of four Laplace interactions, each of which is evaluated using the adaptive fast multipole method (FMM) (Greengard and Rokhlin, 1997) where the exponential expansions are applied to diagonalize the multipole-to-local translation operators. RPYFMM offers a unified execution on both shared and distributed memory computers by leveraging the DASHMM library (DeBuhr et al., 2016, 2018). Preliminary numerical results show that the interactions for a molecular system of 15 million particles (beads) can be computed within one second on a Cray XC30 cluster using 12,288 cores, while achieving approximately 54% strong-scaling efficiency.

Original language	English (US)
Pages (from-to)	99-108
Number of pages	10
Journal	Computer Physics Communications
Volume	227
DOIs	https://doi.org/10.1016/j.cpc.2018.02.005
State	Published - Feb 16 2018
Externally published	Yes

Bibliographical note

KAUST Repository Item: Exported on 2022-06-08
Acknowledgements: The authors gratefully acknowledge the inspiring discussions with Profs. David Keyes and Rio Yokota on different parallelization strategies for our solver. BZ was supported in part by National Science Foundation Grant Number ACI-1440396. GH was supported in part by National Institute of Health Grant Number GM 31749. This research was supported in part by Lilly Endowment, Inc., through its support for the Indiana University Pervasive Technology Institute. Part of the work was finished when JH was a visiting professor at the King Abdullah University of Science and Technology.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

ASJC Scopus subject areas

Hardware and Architecture
General Physics and Astronomy

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10.1016/j.cpc.2018.02.005

Cite this

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title = "RPYFMM: Parallel adaptive fast multipole method for Rotne–Prager–Yamakawa tensor in biomolecular hydrodynamics simulations",

abstract = "RPYFMM is a software package for the efficient evaluation of the potential field governed by the Rotne–Prager–Yamakawa (RPY) tensor interactions in biomolecular hydrodynamics simulations. In our algorithm, the RPY tensor is decomposed as a linear combination of four Laplace interactions, each of which is evaluated using the adaptive fast multipole method (FMM) (Greengard and Rokhlin, 1997) where the exponential expansions are applied to diagonalize the multipole-to-local translation operators. RPYFMM offers a unified execution on both shared and distributed memory computers by leveraging the DASHMM library (DeBuhr et al., 2016, 2018). Preliminary numerical results show that the interactions for a molecular system of 15 million particles (beads) can be computed within one second on a Cray XC30 cluster using 12,288 cores, while achieving approximately 54% strong-scaling efficiency.",

author = "W. Guan and X. Cheng and J. Huang and G. Huber and W. Li and McCammon, {J. A.} and B. Zhang",

note = "KAUST Repository Item: Exported on 2022-06-08 Acknowledgements: The authors gratefully acknowledge the inspiring discussions with Profs. David Keyes and Rio Yokota on different parallelization strategies for our solver. BZ was supported in part by National Science Foundation Grant Number ACI-1440396. GH was supported in part by National Institute of Health Grant Number GM 31749. This research was supported in part by Lilly Endowment, Inc., through its support for the Indiana University Pervasive Technology Institute. Part of the work was finished when JH was a visiting professor at the King Abdullah University of Science and Technology. This publication acknowledges KAUST support, but has no KAUST affiliated authors.",

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AU - Huber, G.

AU - Li, W.

AU - McCammon, J. A.

AU - Zhang, B.

N1 - KAUST Repository Item: Exported on 2022-06-08 Acknowledgements: The authors gratefully acknowledge the inspiring discussions with Profs. David Keyes and Rio Yokota on different parallelization strategies for our solver. BZ was supported in part by National Science Foundation Grant Number ACI-1440396. GH was supported in part by National Institute of Health Grant Number GM 31749. This research was supported in part by Lilly Endowment, Inc., through its support for the Indiana University Pervasive Technology Institute. Part of the work was finished when JH was a visiting professor at the King Abdullah University of Science and Technology. This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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N2 - RPYFMM is a software package for the efficient evaluation of the potential field governed by the Rotne–Prager–Yamakawa (RPY) tensor interactions in biomolecular hydrodynamics simulations. In our algorithm, the RPY tensor is decomposed as a linear combination of four Laplace interactions, each of which is evaluated using the adaptive fast multipole method (FMM) (Greengard and Rokhlin, 1997) where the exponential expansions are applied to diagonalize the multipole-to-local translation operators. RPYFMM offers a unified execution on both shared and distributed memory computers by leveraging the DASHMM library (DeBuhr et al., 2016, 2018). Preliminary numerical results show that the interactions for a molecular system of 15 million particles (beads) can be computed within one second on a Cray XC30 cluster using 12,288 cores, while achieving approximately 54% strong-scaling efficiency.

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RPYFMM: Parallel adaptive fast multipole method for Rotne–Prager–Yamakawa tensor in biomolecular hydrodynamics simulations

Abstract

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