Abstract

The purpose of this research is to determine the effectiveness of Star-P as a tool for exploiting parallelism in high-performance scientific computing, and eventually contributing to its functionality perhaps by porting it to run on other high performance platforms such as graphics processors. The most attractive feature of Star-P is that it allows researchers and scientists to produce code which is capable of running on high-performance parallel machines, without having to consider concepts related to parallelism or even leave the familiarity of their Matlab environment.

Notes

Poster presented at the 2007 Thrust R3B Solutionware Tools Conference

Keywords

Parallelization, Star-P, Matlab

Subject Categories

Parallel programming (Computer science)

Disciplines

Computer Engineering

Publisher

Bernard M. Gordon Center for Subsurface Sensing and Imaging Systems (Gordon-CenSSIS)

Publication Date

2007

Rights Holder

Bernard M. Gordon Center for Subsurface Sensing and Imaging Systems (Gordon-CenSSIS)

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