Enabling a High Throughput Real Time Data Pipeline for a Large Radio Telescope Array with GPUs
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Enabling a High Throughput Real Time Data Pipeline for a Large Radio Telescope Array with GPUs
| Title: | Enabling a High Throughput Real Time Data Pipeline for a Large Radio Telescope Array with GPUs |
| Author: |
Pfister, Hanspeter; Edgar, Richard G; Mitchell, Daniel A; Ord, Stephen M; Greenhill, Lincoln J.; Clark, Michael A.; Dale, Kevin; Wayth, Randall B.
Note: Order does not necessarily reflect citation order of authors. |
| Citation: | Edgara, Richard G., Michael A. Clark, Kevin Dale, Daniel A. Mitchell, Stephen M. Ord, Randall B. Wayth, Hanspeter Pfister, and Lincoln J. Greenhill. 2010. Enabling a high throughput real time data pipeline for a large radio telescope array with GPUs. Computer Physics Communications 181(10): 1707-1714. |
| Full Text & Related Files: |
CPC_2010.pdf (2.995Mb; PDF) 
|
| Abstract: | The Murchison Widefield Array (MWA) is a next-generation radio telescope currently under construction in the remote Western Australia Outback. Raw data will be generated continuously at 5 GiB s\(^{−1}\), grouped into 8 s cadences. This high throughput motivates the development of on-site, real time processing and reduction in preference to archiving, transport and off-line processing. Each batch of 8 s data must be completely reduced before the next batch arrives. Maintaining real time operation will require a sustained performance of around 2.5 TFLOP s\(^{−1}\) (including convolutions, FFTs, interpolations and matrix multiplications). We describe a scalable heterogeneous computing pipeline implementation, exploiting both the high computing density and FLOP-per-Watt ratio of modern GPUs. The architecture is highly parallel within and across nodes, with all major processing elements performed by GPUs. Necessary scatter-gather operations along the pipeline are loosely synchronized between the nodes hosting the GPUs. The MWA will be a frontier scientific instrument and a pathfinder for planned peta- and exascale facilities. |
| Published Version: | doi:10.1016/j.cpc.2010.06.019 |
| Other Sources: | http://gvi.seas.harvard.edu/sites/all/files/CPC_2010.pdf |
| Terms of Use: | This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP |
| Citable link to this page: | http://nrs.harvard.edu/urn-3:HUL.InstRepos:5344187 |
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Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
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