Translating chapel to use FREERIDE: A case study in using an HPC language for data-intensive computing

Bin Ren, Gagan Agrawal, Brad Chamberlain, Steve Deitz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In the last few years, the growing significance of data-intensive computing has been closely tied to the emergence and popularity of new programming paradigms for this class of applications, including Map-Reduce, and new high-level languages for data-intensive computing. The ultimate goal of these efforts in data-intensive computing has been to achieve parallelism with as little effort as possible, while supporting high efficiency and scalability. While these are also the goals that the parallel language/compiler community has tried meeting for the past several decades, the development of languages and programming systems for data-intensive computing has largely been in isolation to the developments in general parallel programming. Such independent developments in the two areas, i.e., dataintensive computing and high productivity languages lead to the following questions: I) Are HPC languages suitable for expressing data-intensive computations? and if so, II.a) What are the issues in using them for effective parallel programming? or, if not, II.b) What characteristics of data-intensive computations force the need for separate language support?. This paper takes a case study to address these questions. Particularly, we study the suitability of Chapel for expressing dataintensive computations. We also examine compilation techniques required for directly invoking a data-intensive middleware from Chapel's compilation system. The data-intensive middleware we use in this effort is FREERIDE that has been developed at Ohio State. We show how certain transformations can enable efficient invocation of the FREERIDE functions from the Chapel compiler. Our experiments show that after certain optimizations, the performance of the version of Chapel compiler that invokes FREERIDE functions is quite comparable to the performance of hand-written data-intensive applications.

Original languageEnglish (US)
Title of host publication2011 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum, IPDPSW 2011
Pages1242-1249
Number of pages8
DOIs
StatePublished - 2011
Externally publishedYes
Event25th IEEE International Parallel and Distributed Processing Symposium, Workshops and Phd Forum, IPDPSW 2011 - Anchorage, AK, United States
Duration: May 16 2011May 20 2011

Publication series

NameIEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum

Conference

Conference25th IEEE International Parallel and Distributed Processing Symposium, Workshops and Phd Forum, IPDPSW 2011
CountryUnited States
CityAnchorage, AK
Period5/16/115/20/11

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Software
  • Theoretical Computer Science

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