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/

Performance, Maintainability and Scalability of In-Silico Experimental Evolution Simulation (PMSISEE)

Overview

The goal of PMSISEE is to support the collaboration between the Avalon (LIP) and Beagle (LIRIS) teams through research activities on programming modelsand tools for HPC applied to the Aevol/R-Aevol simulator of in silico evolution of bacteria.

Scientific objective

A population of organisms adapting to a new environment is a dynamic system changing over time at many levels (molecules, networks, individuals, ecosystems). A large amount of empirical and theoretical evidence indicates that in real populations all these levels interact, making the dynamics of adaptation a highly complex phenomenon. In order to understand bacterial evolution, we need large-scale integrative models in which all relevant levels from the molecule to the ecology are simulated. The Aevol/R-Aevol simulator (http://www.aevol.fr) has been developed by the Beagle team to address such questions. Aevol integrates the molecular and cellular levels to address the evolution of genomic complexity. R-Aevol adds the network level to investigate the evolution of network complexity.

Challenges

In this project we consider the Aevol/R-Aevol simulator, or equivalent code, as the object of the study. At a first glance, it is characterized by several properties: the code is complex due the models to integrate; the amount of computational resources required for simulations is huge when considering the size of the systems (millions of base pairs in the genome, thousands of genes in the genetic network, billions of individuals in the population, billions of generations); load unbalance occurs when running the models under different conditions ( i.e., different parameters). Any gain in performance, will make these simulations very valuable to understand bacterial evolution and to have feedback on the biological models in order to improve them.

The research during the PMSISEE project will be restricted to two main issues related to the software and its algorithms: 1/ analysis and design of specialized models to tackle software complexity in the context of HPC using next generation of parallel supercomputers. This point is based on advances in software engineering of these last twenty years in particular with respect to code composability and re-use using component model; 2/ performance analysis and design of new, or improvement of existing, algorithms for scalable and efficient simulation of evolving bacterial populations on modern parallel architecture. This axis will deal with heuristics for scheduling in order to well balance the work load and reducing communication.

Inria Project Lab Discovery

Distributed and COoperative management of Virtual Environments autonomousLY

The DISCOVERY initiative aims at exploring a new way of operating Utility Computing (UC) resources.

To accommodate the ever-increasing demand for Utility Computing (UC) resources, while taking into account both energy and economical issues, the current trend consists in building larger and larger data centers in a few strategic locations. Although such an approach enables UC providers to cope with the actual demand while continuing to operate UC resources through centralized software system, it is far from delivering sustainable and efficient UC infrastructures. We claim that a disruptive change in UC infrastructures is required: UC resources should be managed differently, considering locality as a primary concern. To this aim, we propose to leverage any facilities available through the Internet in order to deliver widely distributed UC platforms that can better match the geographical dispersal of users as well as the unending demand. Critical to the emergence of such locality-based UC (LUC) platforms is the availability of appropriate operating mechanisms. We advocate the implementation of a unified system driving the use of resources at an unprecedented scale by turning a complex and diverse infrastructure into a collection of abstracted computing facilities that is both easy to operate and reliable.

Start Date: January 2015

Duration: 4 years

Avalon Members: J. Darrous, G. Fedak, C. Perez

More information on Discovery website

PIA ELCI

ELCI is a French software project that brings together academic and industrial partners to design and provide a software environment for the next generation of HPC systems. The principal objective for the project is to facilitate the development of a software environment that meets the demands of the new generation of HPC architectures. This will cover the whole software stack (system and programming environments), numerical solvers and pre/post/co processing software.
ELCI is a French software project that brings together academic and industrial partners to design and provide a software environment for the next generation of HPC systems. The project is funded by the participating partners and by the French FSN “Fond pour la Société Numérique”.

The principal objective for the project is to facilitate the development of a software environment that meets the demands of the new generation of HPC architectures. This will cover the whole software stack (system and programming environments), numerical solvers and pre/post/co processing software.

A co-design approach is employed, that covers the software environment for computer architectures, the requirements of more demanding applications, and is adapted to future hardware architectures (multicore/many core processors, high-speed networks and data storage).

These developments will be validated according to their capacity to deal with the new exascale challenges- larger scalability, higher resiliency, greater security, improved modularity, with better abstraction and interactivity for application cases.

Start Date: September 2014

Duration: 3 years

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

More information on the ELCI web site.

Inria Project Lab HAC-SPECIS

HAC SPECIS: Inria project lab on High-performance Application and Computers: Studying PErformance and Correctness In Simulation (2016-2020) :

The goal of the HAC SPECIS (High-performance Application and Computers: Studying PErformance and Correctness In Simulation) project is to answer  methodological needs of HPC application and runtime developers and to allow to study real HPC systems both from the correctness and performance point of view. To this end, we gather experts from the HPC, formal verification and performance evaluation community. website : http://hacspecis.gforge.inria.fr/

 

Start Date: June 2016

Duration:

Avalon Members: F. Suter, L. Lefevre

CeoE H2020 POP

Summary

Inaugurated October 1, 2015, the new EU H2020 Center of Excellence (CoE) for Performance Optimisation and Productivity (POP) provides performance optimisation and productivity services for academic and industrial codes. European’s leading experts from the High Performance Computing field will help application developers getting a precise understanding of application and system behaviour. This project is supported by the European Commission under H2020 Grant Agreement No. 676553

Established codes, but especially codes never undergone any analysis or performance tuning, may profit from the expertise of the POP services which use latest state-of-the-art tools to detect and locate bottlenecks in applications, suggest possible code improvements, and may even help by Proof-of-Concept experiments and mock-up test for customer codes on their own platforms.

Partners

Barcelona Supercomputing Centre (BSC), High Performance Computing Center Stuttgart of the University of Stuttgart (HLRS), Jülich Supercomputing Centre (JSC), Numerical Algorithm Group (NAG), Rheinisch-Westfälische Technische Hochschule Aachen (RWTH), TERATEC (TERATEC).

Project Information

Start Date: October 2015

Duration: 3 yars

Avalon Members:

Online Resources

More information on http://www.pop-coe.eu

Labex MILYON

Laboratoire d’excellence en mathématiques et informatique fondamentale.

MILYON fédère les communautés mathématiques et informatique de Lyon autour de trois axes : la recherche d’excellence, notamment des domaines à l’interface des deux disciplines ou d’autres sciences ; la formation, avec l’appui à des filières innovantes tournées vers la recherche ; la société, à travers la médiation de la culture scientifique auprès du grand public et le transfert de technologie vers l’industrie.

Il regroupe plus de 350 chercheurs, et trois unités mixtes de recherche de l’Université de Lyon : l’Institut Camille Jordan, le Laboratoire de l’Informatique du Parallélisme et l’Unité de Mathématiques Pures et Appliquées.

Plus d’information sur le site de MILYON.

Start Date:

Duration:

Avalon Members:

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

Labex PRIMES

Laboratory of Excellence on Physics, Radiobiology, Medical Imaging, and Simulation

The program Laboratory of Excellence (LabEx) aims to endow with significant means a set of research units in order to attract world-renowned researchers and to establish a high-level and integrated politic of research, training and valorization. The ambition of this program is to develop scientific originality, to favor multidisciplinary, to increase the excellence and the international visibility of the French research and to play a driving role into the training of both doctorate and master levels.

PRIMES’s (Physics, Radiobiology, Medical Imaging, and Simulation) primary objective is to develop new concepts and methods for the exploration, the diagnosis and the therapy of cancer and ageing-related pathologies. PRIMES brings together the complementary skills of 16 recognized academic and medical partners with a long-standing experience to develop state-of-the-art methods, covering all necessary fields, from basic physics, instrumentation, radiobiology, data acquisition and processing, to image reconstruction, simulations and modeling supported by supercomputing.

Start Date:

Duration:

Avalon Members:

More information on the PRIME website.

ANR MOEBUS

Multi-objective scheduling for large scale parallel systems.

The MOEBUS project focuses on the efficient execution of parallel applications submitted by various users and sharing resources in large-scale high-performance computing environments.

We propose to investigate new functionalities to add at low cost in actual large scale schedulers and programming standards, for a better use of the resources according to various objectives and criteria. We also propose to revisit the principles of existing schedulers after studying the main factors impacted by job submissions. Then, we will propose novel efficient algorithms for optimizing the schedule for unconventional objectives like energy consumption and to design provable approximation multi-objective optimization algorithms for some relevant combinations of objectives (performance, fairness, energy consumption, etc.). An important characteristic of the project is its right balance between theoretical analysis and practical implementation. The most promising ideas will lead to integration in reference systems such as SLURM and OAR as well as new features in programming standards implementations such as MPI or OpenMP. We expect MOEBUS results to impact further use of very large scale parallel platforms.

Start Date:

Duration:

Avalon Members:

More on MEBUS website