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Synthèse de code hybride à partir d'un programme à mémoire purement distribuée

Synthèse de code hybride à partir d'un programme à mémoire purement distribuée

Hybrid code synthesis from a pure distributed memory program

Proposition de thèse

Spécialité

Informatique temps réel, robotique et automatique - Fontainebleau

Ecole doctorale

SMI - Sciences des Métiers de l'Ingénieur

Directeur de thèse

TADONKI Claude

Unité de recherche

Mathématiques et Systèmes

ContactClaude TADONKI
Site Web
Mots-clés

parallélisme, mémoire

parallelism, memory

Résumé

With the advent of multicore architectures we need us to reconsider the way we organize the tasks of our parallel code and plan their cooperation. Current (and future) supercomputers are built up with multicore processors probably coupled with accelerators such as GPUs. Regarding the connectivity, latency and network bandwidth have certainly evolved significantly, but the gap between the virtual topology and physical topology greatly increases the effective cost of interprocessor communications, especially for applications involving a high connectivity like stencil computation. Therefore, it becomes crucial to really consider hybrid implementations, which consider distributed memory model on top and shared memory model on the nodes. However, several factors are likely to discourage this effort: the required skill to design and implement hybrid codes is not common; in addition, number of quite complex codes have already been written based on the distributed memory model exclusively, and it is hard to consider modifying them; moreover, the belief of a clear effective reward from a hybrid code is moderate, because getting a benefit as close as expected is indeed not trivial. Therefore, designing a quasi-systematic methodology and a corresponding framework, that allow to easily switching from a pure MPI code to an efficient corresponding MPI + OpenMP version would be a valuable contribution. In this thesis, we propose to tackle the problem quite rigorously, on the basis of a tasks graph model and a clearly quantified accounting of major hardware and network aspects. The first goal will be to understand the criteria for an efficient and scalable hybrid code, followed by a methodology for a quick and pragmatic implementation. Applications envisaged for conducting this study are: Lattice QCD; pattern matching on a large sequence of high resolution images; partial differential equations; shortest paths computation in a graph.

With the advent of multicore architectures we need us to reconsider the way we organize the tasks of our parallel code and plan their cooperation. Current (and future) supercomputers are built up with multicore processors probably coupled with accelerators such as GPUs. Regarding the connectivity, latency and network bandwidth have certainly evolved significantly, but the gap between the virtual topology and physical topology greatly increases the effective cost of interprocessor communications, especially for applications involving a high connectivity like stencil computation. Therefore, it becomes crucial to really consider hybrid implementations, which consider distributed memory model on top and shared memory model on the nodes. However, several factors are likely to discourage this effort: the required skill to design and implement hybrid codes is not common; in addition, number of quite complex codes have already been written based on the distributed memory model exclusively, and it is hard to consider modifying them; moreover, the belief of a clear effective reward from a hybrid code is moderate, because getting a benefit as close as expected is indeed not trivial. Therefore, designing a quasi-systematic methodology and a corresponding framework, that allow to easily switching from a pure MPI code to an efficient corresponding MPI + OpenMP version would be a valuable contribution. In this thesis, we propose to tackle the problem quite rigorously, on the basis of a tasks graph model and a clearly quantified accounting of major hardware and network aspects. The first goal will be to understand the criteria for an efficient and scalable hybrid code, followed by a methodology for a quick and pragmatic implementation. Applications envisaged for conducting this study are: Lattice QCD; pattern matching on a large sequence of high resolution images; partial differential equations; shortest paths computation in a graph.

Contexte

Parallélisme

Encadrement

Claude Tadonki, CRI, Centre de recherche en informatique

Profil candidat

Please send a CV, a motivation letter, the list of grades for your last academic year and 1 or 2 recommendation letters.

Please see description in French

Objectif

Innovation

Références

-

Type financement

Concours pour un contrat doctoral

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