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dc.contributor.authorFletcher, Mary
Jin, Guohua
Kennedy, Ken
McCosh, Cheryl
dc.date.accessioned 2017-08-02T22:03:04Z
dc.date.available 2017-08-02T22:03:04Z
dc.date.issued 2006-10-31
dc.identifier.urihttps://hdl.handle.net/1911/96354
dc.description.abstract Matlab is one of the most popular computer languages for technical and scientific programming. However, until recently, it has been limited to running on uniprocessors. One strategy for overcoming this limitation is to introduce global distributed arrays, with those arrays distributed across the processors of a parallel machine. In this paper, we describe the compilation technology we have designed for Matlab D, a distributed-array extension of Matlab. Our approach is distinguished by a two-phase compilation technology with support for a rich collection of data distributions. By precompiling array operations and communication steps into Fortran plus MPI, the time to compile an application using those operations is significantly reduced. This paper includes preliminary results that demonstrate that this approach can dramatically improve performance, scaling well to at least 32 processors.
dc.format.extent 4 pp
dc.language.iso eng
dc.rights You are granted permission for the noncommercial reproduction, distribution, display, and performance of this technical report in any format, but this permission is only for a period of forty-five (45) days from the most recent time that you verified that this technical report is still available from the Computer Science Department of Rice University under terms that include this permission. All other rights are reserved by the author(s).
dc.title Compiling Parallel Matlab for General Distributions Using Telescoping Languages
dc.type Technical report
dc.date.note October 31, 2006
dc.identifier.digital TR06-881
dc.type.dcmi Text
dc.identifier.citation Fletcher, Mary, Jin, Guohua, Kennedy, Ken, et al.. "Compiling Parallel Matlab for General Distributions Using Telescoping Languages." (2006) https://hdl.handle.net/1911/96354.


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