Computer simulation of liquids
Computer simulation of liquids
The Art of Molecular Dynamics Simulation
The Art of Molecular Dynamics Simulation
Cg: a system for programming graphics hardware in a C-like language
ACM SIGGRAPH 2003 Papers
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ACM SIGGRAPH 2004 Papers
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VR '05 Proceedings of the 2005 IEEE Conference 2005 on Virtual Reality
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IEEE Computer Graphics and Applications
General purpose molecular dynamics simulations fully implemented on graphics processing units
Journal of Computational Physics
GPU accelerated Monte Carlo simulation of the 2D and 3D Ising model
Journal of Computational Physics
Towards Large-Scale Molecular Dynamics Simulations on Graphics Processors
BICoB '09 Proceedings of the 1st International Conference on Bioinformatics and Computational Biology
GPU-accelerated molecular dynamics simulation for study of liquid crystalline flows
Journal of Computational Physics
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Journal of Signal Processing Systems
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Computers & Geosciences
GPU accelerated simulations of 3D deterministic particle transport using discrete ordinates method
Journal of Computational Physics
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ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part III
Multi-level Parallelism for Time- and Cost-Efficient Parallel Discrete Event Simulation on GPUs
PADS '12 Proceedings of the 2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation
On-Board Multi-GPU molecular dynamics
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
The Journal of Supercomputing
Hi-index | 31.47 |
Molecular dynamics (MD) simulations have become a powerful tool for elucidating complex physical phenomena. However, MD method is very time-consuming. This paper presents a method to accelerate computation of MD simulation. The acceleration is achieved by take advantage of modern graphics processing units (GPU). As an example, the thermal conductivities of solid argon were calculated with the GPU-based MD algorithm. The test results indicated that the GPU-based implementation is faster than that of CPU-based one. The speedup of a factor between 10 and 11 is realized.