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Thèse de

Maxime Hugues

vendredi 13 mai 2011

Un Paradigme de Programmation Multi-Niveaux pour le Calcul Numérique sur les Machines Post-Petascales et Exascales

Directeur de Thèse : Serge Petiton, Professeur, Université Lille 1
Rapporteurs : Mitsuhisa Sato, Professeur, Université de Tsukuba (Japon)
Michel Daydé, Professeur, ENSEEIHT-IRIT, Toulouse
Membres : Nouredine Melab, Professeur, Université Lille 1
Peter Arbenz, Professeur, ETH Zürich (Suisse)
Jean-Patrick Mascomere, TOTAL

The coming of post-petscale and exascale supercomputers offers the perspective to accelerate the solving of engineering problems and to highly complex modeling. However, these future systems challenge computer scientists to built such machines. Many issues must be faced such as fault-tolerance, energy consumption and the programming of these complex systems composed of billion cores.

In this thesis, we have focused on the programming aspect and propose a multi-level programming paradigm composed of three levels. For the low level, a data parallel paradigm is proposed to program many-cores processors for its focus on data mapping and movements. We have implemented and evaluated the SpMV with various sparse matrix formats on GPU to illustrate this point. For the intermediate level, we propose a message passing paradigm in order to optimize inter-sockets and inter-nodes communications. For the high level, a graph description paradigm is proposed to program and manage the parallelism between nodes.

With a dense matrix inversion method developed in YML, we underline the interest of graph for the Time-To-Solution reduction and for the support of asynchronous communications in a transparent way. The interest of graph is also demonstrated for I/O optimizations and for their direct support into the programming model. We finally conclude by analyzing a such proposition of programming paradigm for exascale machines and outlines the future work direction.


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