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:

  • To control large scale, heterogeneous configurations. The point is to propose new models, principles and mechanisms to organize the communications (especially high performance routing in a heterogeneous context), thread scheduling and input/output on this type of architecture, in a way that is simultaneously portable and efficient. We also propose to think about introducing such necessary properties as dynamicity, fault tolerance and scaling into this new runtime generation while minimizing their negative impact on application performance.
  • To optimally exploit new technology. We intend to continue a focused technological watch activity (networks, processors), so as to stay in tune with the actual constraints imposed by production machines, and above all to understand how to make efficient use of such new technology (new paradigms in communication models, thread scheduling strategies, and so on). In this particular point, we intend to work on improving the expressivity of proposed interfaces, that should ideally make it possible to separate application constraints from the optimizations performed by the runtime.
  • To improve the integration into environments and applications. We plan to explore the frontier between runtimes and higher level environments, in order to study even more efficient optimizations. There are several possibilities: extending the environment interfaces that too often encapsulate the underlying runtime interface, exploiting information supplied by a program analyzer with the goal of improving the heuristics used in the runtimes, application code refinements by a specializer using information fed back by the runtime during deployment, and so on.
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.

  • Assisting the development of applications for smart spaces by leveraging dedicated design languages that provide support for each step of the process (programming, test, deployment, …)
  • Ensuring the dependability and the security of smart spaces by integrating non-functional concerns as early as application design time and by guaranteeing their conformance.
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.

  • Design and implement computational kernels for dense and sparse numerical linear algebra as well as for N-body calculations
  • Design effective parallel code coupling techniques
  • Implement multi-scale multi-physics applications