Pseudorandom number generation for Brownian Dynamics and Dissipative Particle Dynamics simulations on GPU devices
Abstract
Highlights: {yields} Molecular Dynamics codes implemented on GPUs have achieved twoorder of magnitude computational accelerations. {yields} Brownian Dynamics and Dissipative Particle Dynamics simulations require a large number of random numbers per time step. {yields} We introduce a method for generating small batches of pseudorandom numbers distributed over many threads of calculations. {yields} With this method, Dissipative Particle Dynamics is implemented on a GPU device without requiring threadtothread communication.  Abstract: Brownian Dynamics (BD), also known as Langevin Dynamics, and Dissipative Particle Dynamics (DPD) are implicit solvent methods commonly used in models of soft matter and biomolecular systems. The interaction of the numerous solvent particles with larger particles is coarsegrained as a Langevin thermostat is applied to individual particles or to particle pairs. The Langevin thermostat requires a pseudorandom number generator (PRNG) to generate the stochastic force applied to each particle or pair of neighboring particles during each time step in the integration of Newton's equations of motion. In a SingleInstructionMultipleThread (SIMT) GPU parallel computing environment, small batches of random numbers must be generated over thousands of threads and millions of kernel calls. In this communication we introduce a onePRNGperkernelcallperthread scheme, in which a microstream of pseudorandom numbers is generated inmore »
 Authors:
 Applied Physics, University of Michigan, Ann Arbor, Michigan 48109 (United States)
 Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109 (United States)
 (United States)
 Publication Date:
 OSTI Identifier:
 21592608
 Resource Type:
 Journal Article
 Resource Relation:
 Journal Name: Journal of Computational Physics; Journal Volume: 230; Journal Issue: 19; Other Information: DOI: 10.1016/j.jcp.2011.05.021; PII: S00219991(11)003329; Copyright (c) 2011 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA)
 Country of Publication:
 United States
 Language:
 English
 Subject:
 97 MATHEMATICAL METHODS AND COMPUTING; ACCELERATION; COMMUNICATIONS; COMPUTERIZED SIMULATION; EQUATIONS OF MOTION; MATHEMATICAL MODELS; MOLECULAR DYNAMICS METHOD; RANDOMNESS; STOCHASTIC PROCESSES; THERMOSTATS; CALCULATION METHODS; CONTROL EQUIPMENT; DIFFERENTIAL EQUATIONS; EQUATIONS; EQUIPMENT; PARTIAL DIFFERENTIAL EQUATIONS; SIMULATION
Citation Formats
Phillips, Carolyn L., Anderson, Joshua A., Glotzer, Sharon C., Email: sglotzer@umich.edu, Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109, and Material Science and Engineering, University of Michigan, Ann Arbor, Michigan 48109. Pseudorandom number generation for Brownian Dynamics and Dissipative Particle Dynamics simulations on GPU devices. United States: N. p., 2011.
Web. doi:10.1016/j.jcp.2011.05.021.
Phillips, Carolyn L., Anderson, Joshua A., Glotzer, Sharon C., Email: sglotzer@umich.edu, Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109, & Material Science and Engineering, University of Michigan, Ann Arbor, Michigan 48109. Pseudorandom number generation for Brownian Dynamics and Dissipative Particle Dynamics simulations on GPU devices. United States. doi:10.1016/j.jcp.2011.05.021.
Phillips, Carolyn L., Anderson, Joshua A., Glotzer, Sharon C., Email: sglotzer@umich.edu, Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109, and Material Science and Engineering, University of Michigan, Ann Arbor, Michigan 48109. Wed .
"Pseudorandom number generation for Brownian Dynamics and Dissipative Particle Dynamics simulations on GPU devices". United States.
doi:10.1016/j.jcp.2011.05.021.
@article{osti_21592608,
title = {Pseudorandom number generation for Brownian Dynamics and Dissipative Particle Dynamics simulations on GPU devices},
author = {Phillips, Carolyn L. and Anderson, Joshua A. and Glotzer, Sharon C., Email: sglotzer@umich.edu and Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109 and Material Science and Engineering, University of Michigan, Ann Arbor, Michigan 48109},
abstractNote = {Highlights: {yields} Molecular Dynamics codes implemented on GPUs have achieved twoorder of magnitude computational accelerations. {yields} Brownian Dynamics and Dissipative Particle Dynamics simulations require a large number of random numbers per time step. {yields} We introduce a method for generating small batches of pseudorandom numbers distributed over many threads of calculations. {yields} With this method, Dissipative Particle Dynamics is implemented on a GPU device without requiring threadtothread communication.  Abstract: Brownian Dynamics (BD), also known as Langevin Dynamics, and Dissipative Particle Dynamics (DPD) are implicit solvent methods commonly used in models of soft matter and biomolecular systems. The interaction of the numerous solvent particles with larger particles is coarsegrained as a Langevin thermostat is applied to individual particles or to particle pairs. The Langevin thermostat requires a pseudorandom number generator (PRNG) to generate the stochastic force applied to each particle or pair of neighboring particles during each time step in the integration of Newton's equations of motion. In a SingleInstructionMultipleThread (SIMT) GPU parallel computing environment, small batches of random numbers must be generated over thousands of threads and millions of kernel calls. In this communication we introduce a onePRNGperkernelcallperthread scheme, in which a microstream of pseudorandom numbers is generated in each thread and kernel call. These high quality, statistically robust microstreams require no global memory for state storage, are more computationally efficient than other PRNG schemes in memorybound kernels, and uniquely enable the DPD simulation method without requiring communication between threads.},
doi = {10.1016/j.jcp.2011.05.021},
journal = {Journal of Computational Physics},
number = 19,
volume = 230,
place = {United States},
year = {Wed Aug 10 00:00:00 EDT 2011},
month = {Wed Aug 10 00:00:00 EDT 2011}
}

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