Team Bacchus

Overall Objectives
Scientific Foundations
Application Domains
New Results
Contracts and Grants with Industry
Other Grants and Activities

Section: Other Grants and Activities

National initiatives

AEROCAV: Experimental and numerical study of the aeroacoustic in cylindric cavities

Participants : Rémi Abgrall [ Corresponding member ] , Mario Ricchiuto, Jiri Trefilik.


Dates: 2006-2009

Partners:Ecole Centrale Lyon, ONERA-DSNA, ENSAM, Université Aix-Marseille

Overview: The AEROCAV project goal is to study the noise produced by the circulation of air around elliptic or cylindric cavities. This kind of noises are particularly intense around aircraft wing at take-off and landing phase. Our task is to analyse new schemes that are high order accurate and can be used on general unstructured meshes. This is done within the framework of residual distribution schemes.

ASTER: Adaptive MHD Simulation of Tokamak Elms for iteR

Participants : Rémi Abgrall, Robin Huart, Pascal Hénon, Pierre Ramet [ Corresponding member ] , Hocine Sellama.

Grant: ANR-06-CIS

Dates: 2006 – 2009

Partners: CEA Cadarache.

Overview: The magneto-hydrodynamic instability called ELM for Edge Localized Mode is commonly observed in the standard tokamak operating scenario. The energy losses the ELM will induce in ITER plasmas are a real concern. However, the current understanding of what sets the size of these ELM induced energy losses is extremely limited. No numerical simulations of the complete ELM instability, from its onset through its non-linear phase and its decay, exist in literature. Recently, encouraging results on the simulation of an ELM cycle have been obtained with the JOREK code developed at CEA but at reduced toroidal resolution. The JOREK code uses a fully implicit time evolution scheme in conjunction with the PaStiX sparse matrix library. In this project it is proposed to develop and implement methods to improve the MHD simulation code to enable high-resolution MHD simulations of ELMs. The ELM simulations are urgently needed to improve our understanding of ELMs and to evaluate possible mechanism to control the energy losses. The improvements include adaptive mesh refinement, a robust numerical MHD scheme and refinable cubic Hermite finite elements. These developments need to be consistent with the implicit time evolution scheme and the PaStiX solver. The implicit scheme is essential due to the large variety of time scales in the MHD simulations. The new methods will be implemented and evaluated in the code FluidBox , developed by the BACCHUS team and the JOREK code to optimize the exchange of expertise on numerical methods and MHD simulations.

The project is a collaboration between the Departement de Recherche sur la Fusion Controlée (DRFC, CEA/Cadarache) and the Laboratoire Bordelais de Recherche en Informatique (LaBRI) and Mathématiques Appliquées de Bordeaux (IMB) at the University of Bordeaux 1.


NUMASIS: adaptation and optimization of the applicative performance on NUMA architectures

Participants : Mathieu Faverge, Abdou Guermouche, Pierre Ramet, Jean Roman [ Team Hiepacs, corresponding member ] .

Grant: ANR-05-CIGC-002

Dates: 2006 – 2009

Partners: Bull, Total, BRGM, CEA, ID-Imag (leader of the project), PARIS (IRISA), Runtime (INRIA Bordeaux Sud-Ouest).

Overview: The multiprocessor machines of tomorrow will rely on an NUMA architecture introducing multiple levels of hierarchy into computers (multimodules, chips multibody, multithreading material, etc). To exploit these architectures, parallel applications must use powerful runtime supports making possible the distribution of execution and data streams without compromising their portability. Project NUMASIS proposes to evaluate the functionalities provided by the current systems, to apprehend the limitations, to design and implement new mechanisms of management of the processes, data and communications within the basic softwares (operating system, middleware, libraries). The target algorithmic tools that we retained are parallel linear sparse solvers with application to seismology.


PETAL: PETascaling ALgorithms for preconditioning used in scientific applications

Participants : Pascal Hénon [ Corresponding member ] , Jun-Ho Her, François Pellegrini, Pierre Ramet.

Grant: ANR Cosinus 2008

Dates: 2009–2011

Partners: INRIA Saclay-Ile de France (leader of the project), Paris 6, IFP (Rueil-Malmaison), CEA Saclay

Overview: In this collaborative effort, we propose to develop parallel preconditioning techniques for the emergent hierarchical models of clusters of multi-core processors, as used for example in future petascale machines. The preconditioning techniques are based on recent progress obtained in combining the well known incomplete LU (ILU) factorization with the tangential filtering, another incomplete factorization where a filtering condition is satisfied. The goal of this project is to transform these preconditioners into black box parallel preconditioners that could be as usable as standard and popular methods such as ILU. For this, we address several issues related to the quality of the combined preconditioner. We also aim to make the connection of these methods with the domain decomposition methods. To obtain a preconditioner suitable for parallelism, we will study associated graph partitioning and reordering techniques.


SOLSTICE: High performance solvers and simulations

Participants : Patrick Amestoy, Sébastien Fourestier, Jérémie Gaidamour, Abdou Guermouche, Pascal Hénon, Jun-Ho Her, François Pellegrini, Pierre Ramet, Jean Roman [ Team Hiepacs, corresponding member ] .

Grant: ANR-06-CIS

Dates: 2006 – 2009


Overview: New advances in high-performance numerical simulation require the continuing development of new algorithms and numerical methods. These technologies must then be implemented and integrated into real-life parallel simulation codes in order to address critical applications that are at the frontier of our know-how. The solution of sparse systems of linear equations of (very) large size is one of the most critical computational kernel in terms of both memory and time requirements. Three-dimensional partial differential equations (3D-PDE) are particularly concerned by the availability of efficient sparse linear algorithms since the numerical simulation process often leads to linear systems of 10 to 100 million variables that need to be solved many times. In a competitive environment where numerical simulation becomes extremely critical compared to physical experimentation, very precise models involving a very accurate discretisation are more and more critical. The objective of our project is thus both to design and develop high-performance parallel linear solvers that will be efficient to solve complex multiphysic and multiscale problems of very large size. To demonstrate the impact of our research, the work produced in the project will be integrated in real simulation codes to perform simulations that could not be considered with today's technologies.



Participants : Rémi Abgrall [ Corresponding member ] , Pascal Jacq.

Grant: Competitivity cluster AESE

Dates: 2006 – 2009


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