KAAPI: A thread scheduling runtime system for data flow computations on cluster of multi-processors

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.
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Communication dans un congrès
2007 international workshop on Parallel symbolic computation, Jul 2007, Waterloo, Canada. ACM, pp.15-23, 2007, 〈10.1145/1278177.1278182〉
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https://hal.inria.fr/hal-00684843
Contributeur : Ist Rennes <>
Soumis le : mardi 3 avril 2012 - 12:12:52
Dernière modification le : vendredi 12 octobre 2018 - 01:18:03

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Thierry Gautier, Xavier Besseron, Laurent Pigeon. KAAPI: A thread scheduling runtime system for data flow computations on cluster of multi-processors. 2007 international workshop on Parallel symbolic computation, Jul 2007, Waterloo, Canada. ACM, pp.15-23, 2007, 〈10.1145/1278177.1278182〉. 〈hal-00684843〉

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