A hybrid performance modeling approach for adaptive algorithm selection on hierarchical clusters

Abstract : Recent advances in parallel and distributed computing have made it very challenging for programmers to reach the performance potential of current systems. In addition, recent advances in numerical algorithms and software optimizations have tremendously increased the number of alternatives for solving a problem, which further complicates the software tuning process. Indeed, no single algorithm can represent the universal best choice for efficient solution of a given problem on all compute substrates. In this paper, we develop a framework that addresses the design of efficient parallel algorithms in hierarchical computing environments. More specifically, given multiple choices for solving a particular problem, the framework uses a judicious combination of analytical performance models and empirical approaches to automate the algorithm selection by determining the most suitable execution scheme expected to perform the best at the specific setting. Preliminary experimental results obtained by implementing two different numerical kernels demonstrated the interest of the hybrid performance modeling approach integrated in the framework.
Type de document :
Communication dans un congrès
IEEE. AICCSA 2010 : IEEE/ACS International Conference on Computer Systems and Applications, May 2010, Hammamet, Tunisia. IEEE, 2010, 〈10.1109/AICCSA.2010.5587043〉
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https://hal.inria.fr/hal-00690492
Contributeur : Ist Rennes <>
Soumis le : lundi 23 avril 2012 - 16:46:41
Dernière modification le : lundi 20 juin 2016 - 14:10:32

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Wahid Nasri, Sami Achour. A hybrid performance modeling approach for adaptive algorithm selection on hierarchical clusters. IEEE. AICCSA 2010 : IEEE/ACS International Conference on Computer Systems and Applications, May 2010, Hammamet, Tunisia. IEEE, 2010, 〈10.1109/AICCSA.2010.5587043〉. 〈hal-00690492〉

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