A Selection theory and methodology for heterogeneous supercomputing

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dc.contributor.author Chen, Song
dc.contributor.author Eshaghian, Mary
dc.contributor.author Khokhar, Ashfaq
dc.contributor.author Shaaban, Muhammad
dc.date.accessioned 2010-02-15T17:25:07Z
dc.date.available 2010-02-15T17:25:07Z
dc.date.issued 1993-04
dc.identifier.citation Proceedings of the Heterogeneous Processing Workshop, April 1993 en_US
dc.identifier.uri http://hdl.handle.net/1850/11556
dc.description.abstract In this paper, a methodology for mapping algorithms onto heterogeneous suite of supercomputers is presented. An approach for selecting an optimal suite of computers for solving problems with diverse computational requirements, called Heterogeneous Optimal Selection Theory (HOST), is presented. HOST is an extension to Augmented Optimal Selection Theory in two ways: It incorporates heterogeneous parallelism embedded in the tasks, and it reflects the costs associated in using various fine grain mapping strategies at individual machine level. The proposed mapping methodology is based on the Cluster-M programming paradigm. For the mapping purpose, the input format, assumed in HOST, is modeled in terms of Hierarchical Cluster-M specification and representation. For a given problem, a Hierarchical Cluster-M specification is generated to indicate the execution of concurrent tasks at different stages of the computation. This specification is then mapped onto the Hierarchical Cluster- M representation of the underlying heterogeneous suite of supercomputers. en_US
dc.language.iso en_US en_US
dc.title A Selection theory and methodology for heterogeneous supercomputing en_US
dc.type Article en_US

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