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Productivity and performance using partitioned global address space languages
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International Conference on Symbolic and Algebraic Computation archive
Proceedings of the 2007 international workshop on Parallel symbolic computation table of contents
London, Ontario, Canada
SESSION: Invited speakers' papers table of contents
Pages: 24 - 32  
Year of Publication: 2007
ISBN:978-1-59593-741-4
Authors
Katherine Yelick  University of California at Berkeley and Lawrence Berkeley National Laboratory
Dan Bonachea  University of California at Berkeley and Lawrence Berkeley National Laboratory
Wei-Yu Chen  University of California at Berkeley and Lawrence Berkeley National Laboratory
Phillip Colella  Lawrence Berkeley National Laboratory
Kaushik Datta  University of California at Berkeley and Lawrence Berkeley National Laboratory
Jason Duell  University of California at Berkeley and Lawrence Berkeley National Laboratory
Susan L. Graham  University of California at Berkeley
Paul Hargrove  University of California at Berkeley and Lawrence Berkeley National Laboratory
Paul Hilfinger  University of California at Berkeley
Parry Husbands  University of California at Berkeley and Lawrence Berkeley National Laboratory
Costin Iancu  Lawrence Berkeley National Laboratory
Amir Kamil  University of California at Berkeley
Rajesh Nishtala  University of California at Berkeley
Jimmy Su  University of California at Berkeley
Michael Welcome  Lawrence Berkeley National Laboratory
Tong Wen  Lawrence Berkeley National Laboratory
Sponsors
SIGSAM: ACM Special Interest Group on Symbolic and Algebraic Manipulation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Partitioned Global Address Space (PGAS) languages combine the programming convenience of shared memory with the locality and performance control of message passing. One such language, Unified Parallel C (UPC) is an extension of ISO C defined by a consortium that boasts multiple proprietary and open source compilers. Another PGAS language, Titanium, is a dialect of JavaTM designed for high performance scientific computation. In this paper we describe some of the highlights of two related projects, the Titanium project centered at U.C. Berkeley and the UPC project centered at Lawrence Berkeley National Laboratory. Both compilers use a source-to-source strategy that trans-lates the parallel languages to C with calls to a communication layer called GASNet. The result is portable high-performance compilers that run on a large variety of shared and distributed memory multiprocessors. Both projects combine compiler, runtime, and application efforts to demonstrate some of the performance and productivity advantages to these languages.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Katherine Yelick: colleagues
Dan Bonachea: colleagues
Wei-Yu Chen: colleagues
Phillip Colella: colleagues
Kaushik Datta: colleagues
Jason Duell: colleagues
Susan L. Graham: colleagues
Paul Hargrove: colleagues
Paul Hilfinger: colleagues
Parry Husbands: colleagues
Costin Iancu: colleagues
Amir Kamil: colleagues
Rajesh Nishtala: colleagues
Jimmy Su: colleagues
Michael Welcome: colleagues
Tong Wen: colleagues