From LaBRI - Laboratoire Bordelais de Recherche en Informatique

Satanas: Satanas

Supports and Algorithms for High Performance Numerical Applications (SATANAS)
Leader : E. JeannotMembres Publications

The SATANAS team is one of the six LaBRI teams. It is mostly focusing on HPC. The team currently gathers researchers belonging to three LaBRI themes which actually correspond to four joint project-teams.

Runtime system.
High Performance Runtime Systems for Parallel Architectures

Leader : Denis BARTHOU [ ]

Joint Project-Teams : STORM and TADAAM

This research theme works in the context of high performance parallel computing. The project is interested in designing and studying principles as well as implementing and evaluating the mechanisms that will be at the heart of tomorrow's parallel runtimes. More precisely, the point is to define, implement and validate a family of generic runtimes that constitute a flexible and efficient basis for the construction of environments/applications in the field of intensive parallel computing. These runtimes should make it possible to efficiently exploit such parallel machines as large scale, multicore, heterogeneous and hierarchical clusters.

Our goal is to meet three major challenges:

Simulation d'un système de gestion de bâtiment à l'aide de l'outil DiaSim.
Language-based approach for orchestrating networked objects

Leader : Charles CONSEL [ ]

Joint Project-Team : PHOENIX

Developing languages and tools for assisting and certifying the design and the programming of applications dedicated to smart spaces.

Simulation en dynamique moléculaire d'une interaction entre un colorant (indigo) et une structure poreuse (argile).
High-End Parallel Algorithms for Challenging Numerical Simulations

Leader : Pierre RAMET [ ]

Joint Project-Team : HIEPACS

Contribute to the design and development of robust simulation tools for heterogeneous many-core extreme scale architectures; analyze and solve computational science challenges for 3D complex academic and industrial applications that require parallel scalable algorithms.

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Page mise à jour le 24/05/2016 à 13:19