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.
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)
Permanent URL
Recommended Citation
Schaa, Dana; Kaeli, David; and Edelman, Alan, "Semi-automated parallelization using Star-P" (2007). Research Thrust R3 Presentations. Paper 15. http://hdl.handle.net/2047/d10009164
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Notes
Poster presented at the 2007 Thrust R3B Solutionware Tools Conference