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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Gang Chen Guobo Li Songwen Pei Baifeng Wu |
| Copyright Year | 2009 |
| Description | Author affiliation: School of Computer Science, Fudan University, Shanghai 200433, China (Gang Chen; Guobo Li; Songwen Pei; Baifeng Wu) |
| Abstract | 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. |
| Starting Page | 113 |
| Ending Page | 118 |
| File Size | 372347 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424435340 |
| DOI | 10.1109/CSCWD.2009.4968044 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-04-22 |
| Publisher Place | Chile |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Acceleration Computational modeling Graphics Costs Physics computing Computer simulation High performance computing Parallel algorithms Arithmetic Biomedical computing Brook+ Molecular dynamics (MD) GPU GPGPU |
| Content Type | Text |
| Resource Type | Article |
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