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2009 13th International Conference on Computer Supported Cooperative Work in Design
GPGPU supported cooperative acceleration in molecular dynamics
Santiago, Chile
April 22-April 24
ISBN: 978-1-4244-3534-0
Gang Chen, School of Computer Science, Fudan University, Shanghai 200433, China
Guobo Li, School of Computer Science, Fudan University, Shanghai 200433, China
Songwen Pei, School of Computer Science, Fudan University, Shanghai 200433, China
Baifeng Wu, School of Computer Science, Fudan University, Shanghai 200433, China
Molecular dynamics simulations have become a significant computational approach to study complicated physical phenomena at the atomic level. Nevertheless, accurate simulations are limited in size and timescale by the available computing resources, which make the simulations very time-consuming. This consequentially leads to tremendous computational requirements. Therefore, the need for speeding up this process is crucial. In this paper, we present a novel implementation to accelerate molecular dynamics simulations with GPGPU (General Purpose Graphics Processing Unit). Our goal is to reduce the total computational time of MD simulations at a very high performance/cost ratio with the introduction of the GPGPU algorithm. This is motivated by their enhanced programmability, attractive cost/performance ratio and incredible growth in speed. To demonstrate that GPGPUs already provide an inexpensive alternative to scientific applications, we have used AMD's Brook+ streaming programming environment to implement a new parallel algorithm. Our experimental results show the novel approach achieves speedup by the factor of fifteen compared to the corresponding sequential implementation.
Citation:
Gang Chen, Guobo Li, Songwen Pei, Baifeng Wu, "GPGPU supported cooperative acceleration in molecular dynamics," cscwd, pp.113-118, 2009 13th International Conference on Computer Supported Cooperative Work in Design, 2009
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