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| Content Provider | ACM Digital Library |
|---|---|
| Author | Seal, Sudip K. Perumalla, Kalyan S. |
| Abstract | The spatial scale, runtime speed and behavioral detail of epidemic outbreak simulations together require the use of large-scale parallel processing. In this paper, an optimistic parallel discrete event execution of a reaction-diffusion simulation model of epidemic outbreaks is presented, with an implementation over the ¿sik simulator. Rollback support is achieved with the development of a novel reversible model that combines reverse computation with a small amount of incremental state saving. Parallel speedup and other runtime performance metrics of the simulation are tested on a small (8,192-core) Blue Gene/P system, while scalability is demonstrated on 65,536 cores of a large Cray XT5 system. Scenarios representing large population sizes (up to several hundred million individuals in the largest case) are exercised. |
| Starting Page | 106 |
| Ending Page | 113 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424472925 |
| DOI | 10.1109/PADS.2010.5471657 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2010-05-17 |
| Access Restriction | Subscribed |
| Subject Keyword | Parallel speedup reversible parallel discrete event execution optimistic parallel discrete event execution spatial scale parallel processing reaction diffusion simulation rollback support |
| Content Type | Text |
| Resource Type | Article |
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