RUMD: A general purpose molecular dynamics package optimized to utilize GPU hardware down to a few thousand particles

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Resumé

RUMD is a general purpose, high-performance molecular dynamics (MD) simulation package running on graphical processing units (GPU’s). RUMD addresses the challenge of utilizing the many-core nature of modern GPU hardware when simulating small to medium system sizes (roughly from a few thousand up to hundred thousand particles).

It has a performance that is comparable to other GPU-MD codes at large system sizes and substantially better at smaller sizes. RUMD is open-source and consists of a library written in C++ and the CUDA extension to C, an easy-to-use Python interface, and a set of tools for set-up and post-simulation data analysis. The paper describes RUMD’s main features, optimizations and performance benchmarks.
OriginalsprogEngelsk
Artikelnummer038
TidsskriftSciPost Physics
Vol/bind3
ISSN2542-4653
DOI
StatusUdgivet - 14 dec. 2017

Citer dette

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title = "RUMD: A general purpose molecular dynamics package optimized to utilize GPU hardware down to a few thousand particles",
abstract = "RUMD is a general purpose, high-performance molecular dynamics (MD) simulation package running on graphical processing units (GPU’s). RUMD addresses the challenge of utilizing the many-core nature of modern GPU hardware when simulating small to medium system sizes (roughly from a few thousand up to hundred thousand particles).It has a performance that is comparable to other GPU-MD codes at large system sizes and substantially better at smaller sizes. RUMD is open-source and consists of a library written in C++ and the CUDA extension to C, an easy-to-use Python interface, and a set of tools for set-up and post-simulation data analysis. The paper describes RUMD’s main features, optimizations and performance benchmarks.",
author = "Nicholas Bailey and Trond Ingebrigtsen and Hansen, {Jesper Schmidt} and Arno Veldhorst and Lasse B{\o}hling and Claire Lemarchand and Olsen, {Andreas Elmerdahl} and Bacher, {Andreas Kvist} and Lorenzo Costigliola and Pedersen, {Ulf R{\o}rb{\ae}k} and Heine Larsen and Dyre, {Jeppe C.} and Thomas Schr{\o}der",
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T1 - RUMD: A general purpose molecular dynamics package optimized to utilize GPU hardware down to a few thousand particles

AU - Bailey, Nicholas

AU - Ingebrigtsen, Trond

AU - Hansen, Jesper Schmidt

AU - Veldhorst, Arno

AU - Bøhling, Lasse

AU - Lemarchand, Claire

AU - Olsen, Andreas Elmerdahl

AU - Bacher, Andreas Kvist

AU - Costigliola, Lorenzo

AU - Pedersen, Ulf Rørbæk

AU - Larsen, Heine

AU - Dyre, Jeppe C.

AU - Schrøder, Thomas

PY - 2017/12/14

Y1 - 2017/12/14

N2 - RUMD is a general purpose, high-performance molecular dynamics (MD) simulation package running on graphical processing units (GPU’s). RUMD addresses the challenge of utilizing the many-core nature of modern GPU hardware when simulating small to medium system sizes (roughly from a few thousand up to hundred thousand particles).It has a performance that is comparable to other GPU-MD codes at large system sizes and substantially better at smaller sizes. RUMD is open-source and consists of a library written in C++ and the CUDA extension to C, an easy-to-use Python interface, and a set of tools for set-up and post-simulation data analysis. The paper describes RUMD’s main features, optimizations and performance benchmarks.

AB - RUMD is a general purpose, high-performance molecular dynamics (MD) simulation package running on graphical processing units (GPU’s). RUMD addresses the challenge of utilizing the many-core nature of modern GPU hardware when simulating small to medium system sizes (roughly from a few thousand up to hundred thousand particles).It has a performance that is comparable to other GPU-MD codes at large system sizes and substantially better at smaller sizes. RUMD is open-source and consists of a library written in C++ and the CUDA extension to C, an easy-to-use Python interface, and a set of tools for set-up and post-simulation data analysis. The paper describes RUMD’s main features, optimizations and performance benchmarks.

U2 - 10.21468/SciPostPhys.3.6.038

DO - 10.21468/SciPostPhys.3.6.038

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JO - SciPost Physics

JF - SciPost Physics

SN - 2542-4653

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