Accelerating dissipative particle dynamics simulations on GPUs: Algorithms, numerics and applications

Tang, Yu-Hang; Karniadakis, George Em

doi:10.1016/j.cpc.2014.06.015

Title: Accelerating dissipative particle dynamics simulations on GPUs: Algorithms, numerics and applications

Journal Article · Mon Jun 23 00:00:00 EDT 2014 · Computer Physics Communications

DOI:https://doi.org/10.1016/j.cpc.2014.06.015· OSTI ID:1565291

^[1]; Karniadakis, George Em ^[1]

Brown Univ., Providence, RI (United States). Division of Applied Mathematics

We present a scalable dissipative particle dynamics simulation code, fully implemented on the Graphics Processing Units (GPUs) using a hybrid CUDA/MPI programming model, which achieves 10-30 times speedup on a single GPU over 16 CPU cores and almost linear weak scaling across a thousand nodes. A unified framework is developed within which the efficient generation of the neighbor list and maintaining particle data locality are addressed. Our algorithm generates strictly ordered neighbor lists in parallel, while the construction is deterministic and makes no use of atomic operations or sorting. Such neighbor list leads to optimal data loading efficiency when combined with a two-level particle reordering scheme. A faster in situ generation scheme for Gaussian random numbers is proposed using precomputed binary signatures. We designed custom transcendental functions that are fast and accurate for evaluating the pairwise interaction. The correctness and accuracy of the code is verified through a set of test cases simulating Poiseuille flow and spontaneous vesicle formation. Computer benchmarks demonstrate the speedup of our implementation over the CPU implementation as well as strong and weak scalability. A large-scale simulation of spontaneous vesicle formation consisting of 128 million particles was conducted to further illustrate the practicality of our code in real-world applications.

View Accepted Manuscript (DOE)

Cite

Export

Save

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)

Sponsoring Organization:: USDOE Office of Science (SC)

OSTI ID:: 1565291

Journal Information:: Computer Physics Communications, Vol. 185, Issue 11; ISSN 0010-4655

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

Citation Metrics:

Cited by: 33 works

Citation information provided by
Web of Science

References (30)

General purpose molecular dynamics simulations fully implemented on graphics processing units Anderson, Joshua A.; Lorenz, Chris D.; Travesset, A. Journal of Computational Physics, Vol. 227, Issue 10 https://doi.org/10.1016/j.jcp.2008.01.047	journal	May 2008
Accelerating molecular modeling applications with graphics processors Stone, John E.; Phillips, James C.; Freddolino, Peter L. Journal of Computational Chemistry, Vol. 28, Issue 16 https://doi.org/10.1002/jcc.20829	journal	January 2007
Accelerating molecular dynamics simulations using Graphics Processing Units with CUDA Liu, Weiguo; Schmidt, Bertil; Voss, Gerrit Computer Physics Communications, Vol. 179, Issue 9 https://doi.org/10.1016/j.cpc.2008.05.008	journal	November 2008
Accelerating molecular dynamic simulation on graphics processing units Friedrichs, Mark S.; Eastman, Peter; Vaidyanathan, Vishal Journal of Computational Chemistry, Vol. 30, Issue 6 https://doi.org/10.1002/jcc.21209	journal	April 2009
Scalable parallel programming with CUDA Nickolls, John; Buck, Ian; Garland, Michael Queue, Vol. 6, Issue 2 https://doi.org/10.1145/1365490.1365500	journal	March 2008
Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 1. Generalized Born Götz, Andreas W.; Williamson, Mark J.; Xu, Dong Journal of Chemical Theory and Computation, Vol. 8, Issue 5 https://doi.org/10.1021/ct200909j	journal	April 2012
DL_POLY_2.0: A general-purpose parallel molecular dynamics simulation package Smith, W.; Forester, T. R. Journal of Molecular Graphics, Vol. 14, Issue 3, p. 136-141 https://doi.org/10.1016/S0263-7855(96)00043-4	journal	June 1996
Fast Parallel Algorithms for Short-Range Molecular Dynamics Plimpton, Steve Journal of Computational Physics, Vol. 117, Issue 1 https://doi.org/10.1006/jcph.1995.1039	journal	March 1995
NAMD2: Greater Scalability for Parallel Molecular Dynamics Kalé, Laxmikant; Skeel, Robert; Bhandarkar, Milind Journal of Computational Physics, Vol. 151, Issue 1 https://doi.org/10.1006/jcph.1999.6201	journal	May 1999
GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit Pronk, Sander; Páll, Szilárd; Schulz, Roland Bioinformatics, Vol. 29, Issue 7 https://doi.org/10.1093/bioinformatics/btt055	journal	February 2013
Mature HIV-1 capsid structure by cryo-electron microscopy and all-atom molecular dynamics Zhao, Gongpu; Perilla, Juan R.; Yufenyuy, Ernest L. Nature, Vol. 497, Issue 7451 https://doi.org/10.1038/nature12162	journal	May 2013
Simulating Microscopic Hydrodynamic Phenomena with Dissipative Particle Dynamics Hoogerbrugge, P. J.; Koelman, J. M. V. A. Europhysics Letters (EPL), Vol. 19, Issue 3 https://doi.org/10.1209/0295-5075/19/3/001	journal	June 1992
Dissipative particle dynamics: Bridging the gap between atomistic and mesoscopic simulation Groot, Robert D.; Warren, Patrick B. The Journal of Chemical Physics, Vol. 107, Issue 11 https://doi.org/10.1063/1.474784	journal	September 1997
Statistical Mechanics of Dissipative Particle Dynamics Español, P.; Warren, P. Europhysics Letters (EPL), Vol. 30, Issue 4 https://doi.org/10.1209/0295-5075/30/4/001	journal	May 1995
Smoothed Particle Hydrodynamics and Its Diverse Applications Monaghan, J. J. Annual Review of Fluid Mechanics, Vol. 44, Issue 1 https://doi.org/10.1146/annurev-fluid-120710-101220	journal	January 2012
Dynamics of multiphase systems with complex microstructure. I. Development of the governing equations through nonequilibrium thermodynamics Sagis, Leonard M. C.; Öttinger, Hans Christian Physical Review E, Vol. 88, Issue 2 https://doi.org/10.1103/PhysRevE.88.022149	journal	August 2013
Shape Transformations of Membrane Vesicles from Amphiphilic Triblock Copolymers: A Dissipative Particle Dynamics Simulation Study Li, Xuejin; Pivkin, Igor V.; Liang, Haojun Macromolecules, Vol. 42, Issue 8 https://doi.org/10.1021/ma9000918	journal	April 2009
Lipid bilayer and cytoskeletal interactions in a red blood cell Peng, Z.; Li, X.; Pivkin, I. V. Proceedings of the National Academy of Sciences, Vol. 110, Issue 33 https://doi.org/10.1073/pnas.1311827110	journal	July 2013
Predicting human blood viscosity in silico Fedosov, D. A.; Pan, W.; Caswell, B. Proceedings of the National Academy of Sciences, Vol. 108, Issue 29 https://doi.org/10.1073/pnas.1101210108	journal	July 2011
Pseudo-random number generation for Brownian Dynamics and Dissipative Particle Dynamics simulations on GPU devices Phillips, Carolyn L.; Anderson, Joshua A.; Glotzer, Sharon C. Journal of Computational Physics, Vol. 230, Issue 19 https://doi.org/10.1016/j.jcp.2011.05.021	journal	August 2011
GPU Accelerated Dissipative Particle Dynamics with Parallel Cell-list Updating Wu, Hao IEIT Journal of Adaptive and Dynamic Computing;, Vol. 2011, Issue 2 https://doi.org/10.5813/www.ieit-web.org/IJADC/2011.2.4	journal	January 2011
Accelerating dissipative particle dynamics with multiple GPUs Wang, Sibo; Xu, Junbo; Wen, Hao Computer Physics Communications, Vol. 184, Issue 11 https://doi.org/10.1016/j.cpc.2013.06.011	journal	November 2013
A computer simulation method for the calculation of equilibrium constants for the formation of physical clusters of molecules: Application to small water clusters Swope, William C.; Andersen, Hans C.; Berens, Peter H. The Journal of Chemical Physics, Vol. 76, Issue 1 https://doi.org/10.1063/1.442716	journal	January 1982
Implementing molecular dynamics on hybrid high performance computers – short range forces Brown, W. Michael; Wang, Peng; Plimpton, Steven J. Computer Physics Communications, Vol. 182, Issue 4 https://doi.org/10.1016/j.cpc.2010.12.021	journal	April 2011
DL: A data layout transformation system for heterogeneous computing Sung, I-Jui; Liu, Geng Daniel; Hwu, Wen-Mei W. 2012 Innovative Parallel Computing (InPar) https://doi.org/10.1109/InPar.2012.6339606	conference	May 2012
A Note on the Generation of Random Normal Deviates Box, G. E. P.; Muller, Mervin E. The Annals of Mathematical Statistics, Vol. 29, Issue 2 https://doi.org/10.1214/aoms/1177706645	journal	June 1958
Poiseuille flow to measure the viscosity of particle model fluids Backer, J. A.; Lowe, C. P.; Hoefsloot, H. C. J. The Journal of Chemical Physics, Vol. 122, Issue 15 https://doi.org/10.1063/1.1883163	journal	April 2005
SPH simulations of time-dependent Poiseuille flow at low Reynolds numbers Sigalotti, Leonardo Di G.; Klapp, Jaime; Sira, Eloy Journal of Computational Physics, Vol. 191, Issue 2 https://doi.org/10.1016/S0021-9991(03)00343-7	journal	November 2003
Dynamics of Domain Growth in Self-Assembled Fluid Vesicles Laradji, Mohamed; Sunil Kumar, P. B. Physical Review Letters, Vol. 93, Issue 19 https://doi.org/10.1103/PhysRevLett.93.198105	journal	November 2004
Negative staining of phospholipids and their structural modification by surface-active agents as observed in the electron microscope Bangham, A. D.; Horne, R. W. Journal of Molecular Biology, Vol. 8, Issue 5 https://doi.org/10.1016/S0022-2836(64)80115-7	journal	January 1964

Cited By (7)

FastNBL: fast neighbor lists establishment for molecular dynamics simulation based on bitwise operations Li, Kun; Li, Shigang; Huang, Shan The Journal of Supercomputing, Vol. 76, Issue 7 https://doi.org/10.1007/s11227-019-02860-3	journal	April 2019
A hybrid molecular dynamics/fluctuating hydrodynamics method for modelling liquids at multiple scales in space and time Korotkin, Ivan; Karabasov, Sergey; Nerukh, Dmitry The Journal of Chemical Physics, Vol. 143, Issue 1 https://doi.org/10.1063/1.4923011	journal	July 2015
Mesoscale modeling of phase transition dynamics of thermoresponsive polymers Li, Zhen; Tang, Yu-Hang; Li, Xuejin Chemical Communications, Vol. 51, Issue 55 https://doi.org/10.1039/c5cc01684c	journal	January 2015
Patient-specific modeling of individual sickle cell behavior under transient hypoxia Li, Xuejin; Du, E.; Dao, Ming PLOS Computational Biology, Vol. 13, Issue 3 https://doi.org/10.1371/journal.pcbi.1005426	journal	March 2017
Correction to: FastNBL: fast neighbor lists establishment for molecular dynamics simulation based on bitwise operations Li, Kun; Li, Shigang; Huang, Shan The Journal of Supercomputing, Vol. 75, Issue 12 https://doi.org/10.1007/s11227-019-02956-w	journal	July 2019
Locality properties of 3D data orderings with application to parallel molecular dynamics simulations Al-Kharusi, Ibrahim; Walker, David W. The International Journal of High Performance Computing Applications, Vol. 33, Issue 5 https://doi.org/10.1177/1094342019846282	journal	January 2019
An Investigation on the Aggregation and Rheodynamics of Human Red Blood Cells Using High Performance Computations Xu, Dong; Ji, Chunning; Avital, Eldad Scientifica, Vol. 2017 https://doi.org/10.1155/2017/6524156	journal	January 2017

Similar Records

Collaborating CPU and GPU for large-scale high-order CFD simulations with complex grids on the TianHe-1A supercomputer

Journal Article · Mon Dec 01 00:00:00 EST 2014 · Journal of Computational Physics · OSTI ID:1565291

Xu, Chuanfu; Deng, Xiaogang; Zhang, Lilun; +9 more

GPU-accelerated red blood cells simulations with transport dissipative particle dynamics

Journal Article · Tue Aug 01 00:00:00 EDT 2017 · Computer Physics Communications · OSTI ID:1565291

Blumers, Ansel L.; Tang, Yu-Hang; Li, Zhen; +2 more

Hands-on Performance Tuning of 3D Finite Difference Earthquake Simulation on GPU Fermi Chipset

Journal Article · Sat Jun 02 00:00:00 EDT 2012 · Procedia Computer Science · OSTI ID:1565291

Zhou, Jun; Unat, Didem; Choi, Dong Ju; +2 more

Related Subjects

97 MATHEMATICS AND COMPUTING
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
Computer Science
Physics
DPD
CUDA
LAMMPS
spontaneous vesicle formation

Accelerating dissipative particle dynamics simulations on GPUs: Algorithms, numerics and applications Tang, Yu-Hang https://doi.org/10.17632/nwjmdv43fn The current record is supplemented by this dataset	dataset	January 2019
Accelerating dissipative particle dynamics simulations on GPUs: Algorithms, numerics and applications Tang, Yu-Hang https://doi.org/10.17632/nwjmdv43fn.1 The current record is supplemented by this dataset	dataset	January 2019

Title: Accelerating dissipative particle dynamics simulations on GPUs: Algorithms, numerics and applications

Citation Formats

References (30)

Cited By (7)

Linked Research (2)

Similar Records

Related Subjects