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KAAPI: A thread scheduling runtime system for data flow computations on cluster of multi-processors
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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: 15 - 23  
Year of Publication: 2007
ISBN:978-1-59593-741-4
Authors
Thierry Gautier  INRIA, projet MOAIS, St Martin, France
Xavier Besseron  INRIA, projet MOAIS, St Martin, France
Laurent Pigeon  INRIA, projet MOAIS, St Martin, France
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

The high availability of multiprocessor clusters for computer science seems to be very attractive to the engineer because,at a first level, such computers aggregate high performances. Nevertheless, obtaining peak performances on irregular applications such as computer algebra problems remains a challenging problem. The delay to access memory is non uniform and the irregularity of computations requires to use scheduling algorithms in order to automatically balance the workload among the processors.

This paper focuses on the runtime support implementation to exploit with great efficiency the computation resources of a multiprocessor cluster. The originality of our approach relies on the implementation of an efficient work-stealing algorithm for a macro data flow computation based on minor extension of POSIX thread interface.


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:
Thierry Gautier: colleagues
Xavier Besseron: colleagues
Laurent Pigeon: colleagues