Section: Partnerships and Cooperations

National Initiatives

ANR

ANR White Project Rescue (2010-2015), 4 years.

The ANR White Project Rescue was launched in November 2010, for a duration of 48 months (and was later extended for 6 additional months, up to June 2015). It gathers three Inria partners (Roma , Grand-Large and Hiepacs) and is led by Roma . The main objective of the project is to develop new algorithmic techniques and software tools to solve the exascale resilience problem. Solving this problem implies a departure from current approaches, and calls for yet-to-be-discovered algorithms, protocols and software tools.

This proposed research follows three main research thrusts. The first thrust deals with novel checkpoint protocols. The second thrust entails the development of novel execution models, i.e., accurate stochastic models to predict (and, in turn, optimize) the expected performance (execution time or throughput) of large-scale parallel scientific applications. In the third thrust, we will develop novel parallel algorithms for scientific numerical kernels.

ANR Project Solhar (2013-2017), 4 years.

The ANR Project Solhar was launched in November 2013, for a duration of 48 months. It gathers five academic partners (the HiePACS, Cepage, Roma and Runtime Inria project-teams, and CNRS-IRIT) and two industrial partners (CEA/CESTA and EADS-IW). This project aims at studying and designing algorithms and parallel programming models for implementing direct methods for the solution of sparse linear systems on emerging computers equipped with accelerators.

The proposed research is organized along three distinct research thrusts. The first objective deals with linear algebra kernels suitable for heterogeneous computing platforms. The second one focuses on runtime systems to provide efficient and robust implementation of dense linear algebra algorithms. The third one is concerned with scheduling this particular application on a heterogeneous and dynamic environment.

Inria Project Lab C2S@Exa - Computer and Computational Scienecs at Exascale

Participants : Olivier Aumage [RUNTIME project-team, Inria Bordeaux - Sud-Ouest] , Jocelyne Erhel [SAGE project-team, Inria Rennes - Bretagne Atlantique] , Philippe Helluy [TONUS project-team, Inria Nancy - Grand-Est] , Laura Grigori [ALPINE project-team, Inria Saclay - Île-de-France] , Jean-Yves L’excellent [ROMA project-team, Inria Grenoble - Rhône-Alpes] , Thierry Gautier [MOAIS project-team, Inria Grenoble - Rhône-Alpes] , Luc Giraud [HIEPACS project-team, Inria Bordeaux - Sud-Ouest] , Michel Kern [POMDAPI project-team, Inria Paris - Rocquencourt] , Stéphane Lanteri [Coordinator of the project] , François Pellegrini [BACCHUS project-team, Inria Bordeaux - Sud-Ouest] , Christian Perez [AVALON project-team, Inria Grenoble - Rhône-Alpes] , Frédéric Vivien [ROMA project-team, Inria Grenoble - Rhône-Alpes] .

Since January 2013, the team is participating to the C2S@Exa http://www-sop.inria.fr/c2s_at_exa Inria Project Lab (IPL). This national initiative aims at the development of numerical modeling methodologies that fully exploit the processing capabilities of modern massively parallel architectures in the context of a number of selected applications related to important scientific and technological challenges for the quality and the security of life in our society. At the current state of the art in technologies and methodologies, a multidisciplinary approach is required to overcome the challenges raised by the development of highly scalable numerical simulation software that can exploit computing platforms offering several hundreds of thousands of cores. Hence, the main objective of C2S@Exa is the establishment of a continuum of expertise in the computer science and numerical mathematics domains, by gathering researchers from Inria project-teams whose research and development activities are tightly linked to high performance computing issues in these domains. More precisely, this collaborative effort involves computer scientists that are experts of programming models, environments and tools for harnessing massively parallel systems, algorithmists that propose algorithms and contribute to generic libraries and core solvers in order to take benefit from all the parallelism levels with the main goal of optimal scaling on very large numbers of computing entities and, numerical mathematicians that are studying numerical schemes and scalable solvers for systems of partial differential equations in view of the simulation of very large-scale problems.