Accelerating molecular dynamics simulations using Graphics Processing Units with CUDA

Liu, Weiguo; Schmidt, Bertil; Voß, Gerrit; Müller‐Wittig, Wolfgang

doi:10.1016/j.cpc.2008.05.008

Cited by 133 publications

(98 citation statements)

References 16 publications

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“…This requirement is relevant even for systems as small as a few thousand particles because many simulation platforms nowadays use limited precision to accelerate molecular dynamics simulations. [16][17][18][19][20][21][22][23] For these, the multigrator provides a way of addressing certain artifacts that arise when barostatting and thermostatting is done for large-dimensional systems or with large relaxation times.…”

Section: Multigrator Decomposition For the Martyna-tobias-kleinmentioning

confidence: 99%

Accurate and efficient integration for molecular dynamics simulations at constant temperature and pressure

Lippert

Predescu

Ierardi

et al. 2013

The Journal of Chemical Physics

175

152

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In molecular dynamics simulations, control over temperature and pressure is typically achieved by augmenting the original system with additional dynamical variables to create a thermostat and a barostat, respectively. These variables generally evolve on timescales much longer than those of particle motion, but typical integrator implementations update the additional variables along with the particle positions and momenta at each time step. We present a framework that replaces the traditional integration procedure with separate barostat, thermostat, and Newtonian particle motion updates, allowing thermostat and barostat updates to be applied infrequently. Such infrequent updates provide a particularly substantial performance advantage for simulations parallelized across many computer processors, because thermostat and barostat updates typically require communication among all processors. Infrequent updates can also improve accuracy by alleviating certain sources of error associated with limited-precision arithmetic. In addition, separating the barostat, thermostat, and particle motion update steps reduces certain truncation errors, bringing the time-average pressure closer to its target value. Finally, this framework, which we have implemented on both general-purpose and special-purpose hardware, reduces software complexity and improves software modularity.

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Section: Multigrator Decomposition For the Martyna-tobias-kleinmentioning

confidence: 99%

Accurate and efficient integration for molecular dynamics simulations at constant temperature and pressure

Lippert

Predescu

Ierardi

et al. 2013

The Journal of Chemical Physics

175

152

View full text Add to dashboard Cite

show abstract

“…In recent years, the computational power of graphics processing units (GPUs) has increased rapidly: the theoretical peak performance for single precision floating-point operations on an amateur's GPU 3 reaches nearly 1 Tflop/s. Compared to a single core of a conventional processor, this gives rise to an expected performance jump of one or two orders of magnitude for many demanding computational problems, fueling the desire to exploit graphics processors for scientific applications.…”

Section: Introductionmentioning

confidence: 99%

Highly accelerated simulations of glassy dynamics using GPUs: Caveats on limited floating-point precision

Colberg

Höfling

2011

Computer Physics Communications

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Modern graphics processing units (GPUs) provide impressive computing resources, which can be accessed conveniently through the CUDA programming interface. We describe how GPUs can be used to considerably speed up molecular dynamics (MD) simulations for system sizes ranging up to about 1 million particles. Particular emphasis is put on the numerical long-time stability in terms of energy and momentum conservation, and caveats on limited floating-point precision are issued. Strict energy conservation over 10 8 MD steps is obtained by double-single emulation of the floating-point arithmetic in accuracy-critical parts of the algorithm. For the slow dynamics of a supercooled binary Lennard-Jones mixture, we demonstrate that the use of single-floating point precision may result in quantitatively and even physically wrong results. For simulations of a Lennard-Jones fluid, the described implementation shows speedup factors of up to 80 compared to a serial implementation for the CPU, and a single GPU was found to compare with a parallelised MD simulation using 64 distributed cores.

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“…186 Worldwide researchers of MD simulations have suggested some algorithms to utilize the GPU architecture and its parallel computation capability that is not the strength of CPU (see Refs. 180 and 187-192 for some of these examples).…”

Section: Computing Based On Gpumentioning

confidence: 99%

Molecular Dynamics Simulation of Iron — A Review

Chui

Liu

et al. 2015

SPIN

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Molecular dynamics (MD) is a technique of atomistic simulation which has facilitated scienti¯c discovery of interactions among particles since its advent in the late 1950s. Its merit lies in incorporating statistical mechanics to allow for examination of varying atomic con¯gurations at nite temperatures. Its contributions to materials science from modeling pure metal properties to designing nanowires is also remarkable. This review paper focuses on the progress of MD in understanding the behavior of iron -in pure metal form, in alloys, and in composite nanomaterials. It also discusses the interatomic potentials and the integration algorithms used for simulating iron in the literature. Furthermore, it reveals the current progress of MD in simulating iron by exhibiting some results in the literature. Finally, the review paper brie°y mentions the development of the hardware and software tools for such large-scale computations.

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Accelerating molecular dynamics simulations using Graphics Processing Units with CUDA

Cited by 133 publications

References 16 publications

Accurate and efficient integration for molecular dynamics simulations at constant temperature and pressure

Accurate and efficient integration for molecular dynamics simulations at constant temperature and pressure

Highly accelerated simulations of glassy dynamics using GPUs: Caveats on limited floating-point precision

Molecular Dynamics Simulation of Iron — A Review

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