Computer Physics Communications Program LibraryPrograms in Physics & Physical Chemistry |

[Licence| Download | New Version Template] aevp_v1_0.tar.gz(43 Kbytes) | ||
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Manuscript Title: GPU accelerated Monte Carlo simulation of Brownian motors dynamics
with CUDA | ||

Authors: J. Spiechowicz, M. Kostur, L. Machura | ||

Program title: poisson, dich | ||

Catalogue identifier: AEVP_v1_0Distribution format: tar.gz | ||

Journal reference: Comput. Phys. Commun. 191(2015)140 | ||

Programming language: CUDA C. | ||

Computer: Any with CUDA-compliant GPU. | ||

Operating system: No limits (tested on Linux). | ||

RAM: Hundreds of megabytes for typical case | ||

Keywords: Stochastic differential equation, Langevin equation, graphics processing unit, GPGPU, NVIDIA, CUDA, numerical simulation, Monte Carlo method, Brownian motor, Gaussian noise, Poissonian noise, dichotomous noise. | ||

PACS: 05.10.Gg, 05.40.-a, 05.40.Ca, 05.40.Jc, 05.60.Cd, 05.60.-k. | ||

Classification: 4.3, 23. | ||

External routines: The NVIDIA CUDA Random Number Generation library (cuRAND) | ||

Nature of problem:Graphics processing unit accelerated numerical simulation of stochastic differential equation. | ||

Solution method:The jump-adapted simplified weak order 2.0 predictor-corrector method is employed to integrate the Langevin equation of motion. Ensemble-averaged quantities of interest are obtained through averaging over multiple independent realizations of the system generated by means of the Monte Carlo method. | ||

Unusual features:The actual numerical simulation runs exclusively on the graphics processing unit using the CUDA environment. This allows for a speedup as large as about 3000 when compared to a typical CPU. | ||

Running time:A few seconds |

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