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MESCAL Research team
Middleware efficiently scalable
- Leader : Bruno Gaujal
- Type : Project team
- Research center(s) : Grenoble
- Field : Networks, Systems and Services, Distributed Computing
- Theme : Distributed and High Performance Computing
- Université Joseph Fourier (Grenoble), Institut polytechnique de Grenoble, CNRS, Laboratoire d'Informatique de Grenoble (LIG) (UMR5217)
Team presentation
The goal of the MESCAL project-team is to design and validate middleware and services in order to efficiently exploit large distributed infrastructures built on aggregation of commodity components and/or commodity clusters at metropolitan, national or international scale. Our applications are intensive scientific computations. The methodology used is based on the design of bricks that scale efficiently, using modeling and performance evaluation. of target architectures, software layers and applications.Research themes
The research efforts of MESCAL are aimed at designing and implementing middleware for clusters and grids that scale efficiently.This includes deployment tools, batch schedulers and distributed file systems. The team's research directions also include modelling, simulation, evaluation and optimization of computation grids and more generally, of large discrete event systems, using deterministic as well as stochastic techniques.International and industrial relations
MESCAL is a partner of the network of excellence CoreGrid as well as of the national initiative Grid 5000. Academic collaborations include the University of Leiden (NL), North Carolina State University (USA) and the universities of Rio Grande Do Sul (Brazil). Our main industrial partners are Bull, France Telecom and MandrakeSoft.Keywords: Grid computing Middleware Performance
Research teams of the same theme :
- ALGORILLE - Algorithms for the Grid
- AVALON - Architecture logicielle et algorithmique pour plateformes orientées service
- CEPAGE - Algorithmics for computationally intensive applications over wide scale distributed platforms
- GRAND-LARGE - Global parallel and distributed computing
- HIEPACS - High-End Parallel Algorithms for Challenging Numerical Simulations
- KERDATA - Scalable Storage for Clouds and Beyond
- MOAIS - PrograMming and scheduling design fOr Applications in Interactive Simulation
- ROMA - Optimisation des ressources : modèles, algorithmes et ordonnancement
- RUNTIME - Efficient runtime systems for parallel architectures
Contact
Team leader
Bruno Gaujal
Tel.: +33 4 76 61 20 58
Secretariat
Tel.: +33 4 76 61 20 82
Find out more
Genealogy
This team follows
Inria
Inria.fr
Inria Channel

See also