Computer Science – Performance
Scientific paper
Jun 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004exa....17..287s&link_type=abstract
Experimental Astronomy, Volume 17, Issue 1-3, pp. 287-297
Computer Science
Performance
4
Correlator, Cots, Streaming Data, High Performance Computing, Parallel Processing
Scientific paper
Moore’s law is best exploited by using consumer market hardware. In particular, the gaming industry pushes the limit of processor performance thus reducing the cost per raw flop even faster than Moore’s law predicts. Next to the cost benefits of Common-Of-The-Shelf (COTS) processing resources, there is a rapidly growing experience pool in cluster based processing. The typical Beowulf cluster of PC’s supercomputers are well known. Multiple examples exists of specialised cluster computers based on more advanced server nodes or even gaming stations. All these cluster machines build upon the same knowledge about cluster software management, scheduling, middleware libraries and mathematical libraries. In this study, we have integrated COTS processing resources and cluster nodes into a very high performance processing platform suitable for streaming data applications, in particular to implement a correlator. The required processing power for the correlator in modern radio telescopes is in the range of the larger supercomputers, which motivates the usage of supercomputer technology. Raw processing power is provided by graphical processors and is combined with an Infiniband host bus adapter with integrated data stream handling logic. With this processing platform a scalable correlator can be built with continuously growing processing power at consumer market prices.
Overeem Ruud
Schaaf Kjeld
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