Associated joint team between Avalon and RDI2 Lab. in Rutgers University

  Associated joint team between Avalon and RDI2 Lab. in Rutgers University on   Sustainable Ultra Scale compuTing, dAta and energy Management

The collaboration proposed by the SUSTAM associate team focuses on aspects of sustainability in ultra-scale systems. Launched in 2017, the SUSTAM associated team aims to design a multi-criteria orchestration framework that manages resources, data and energy consumption in an efficient manner. The SUSTAM associate team will enable a long-term collaboration between the Inria Avalon and the RDI² team (Rutgers University . It will allow the teams to coordinate efforts and pursue common research activities in topics such as sustainable software solutions, resource and big-data management, elasticity of stream and batch applications, and energy efficiency. The involved members will contribute to the design of a common architecture and framework with components and algorithms adapted to various contexts.

Web Site: http://avalon.ens-lyon.fr/sustam/

Inria-Illinois-ANL-BSC-JSC-Riken/AICS Joint Laboratory on Extreme Scale Computing

In June 2014, The University of Illinois at Urbana-Champaign, Inria, the French national computer science institute, Argonne National Laboratory, Barcelona Supercomputing Center, Jülich Supercomputing Centre and the Riken Advanced Institute for Computational Science formed the Joint Laboratory for Extreme Scale Computing, a follow-up of the Inria-Illinois Joint Laboratory for Petascale Computing.

Research areas include:

  • Scientific applications (big compute and big data) that are the drivers of the research in the other topics of the joint-laboratory.
  • Modeling and optimizing numerical libraries, which are at the heart of many scientific applications.
  • Novel programming models and runtime systems, which allow scientific applications to be updated or reimagined to take full advantage of extreme-scale supercomputers.
  • Resilience and Fault-tolerance research, which reduces the negative impact when processors, disk drives, or memory fail in supercomputers that have tens or hundreds of thousands of those components.
  • I/O and visualization, which are important part of parallel execution for numerical silulations and data analytics.
  • HPC Clouds, that may execute a portion of the HPC workload in the near future.

More on the lab website

Start Date: 2014

Duration: 4 years

Avalon Members: T. Gautier, L. Lefevre, C. Perez, I. Rais, J. Richard