Research

Research

You can find here an overview of my research, the list of my PhD students, and a list and description of the projects I am/was involved in Overview An overview of my research work is available in my Habilitation (document in french) or in the associated slides (slides in french), defended on 12th Nov 2015 My focus is on Energy Efficiency in ICT and with ICT. I mainly focuses on HPC and large scale infrastructures (clusters, grids, clouds).

Dissemination

List of talks, tutorials, and other presentations 2023 4 May 2023 Comment évaluer / réduire / optimiser la consommation d’énergie dans les Data Center / Cloud instances et l’impact sur l’environnement slides part1 and slides part2, industrial presentation. 1 April 2023 Kickoff ANR Delight WP1 Computational methods for estimating energy expenditure in FL architecture slides, Grid5000 slides, Energy Efficiency in ICT slides 13 Mar 2023 Science du numérique : Numérique et changement climatique slides 10 Jan 2023 Grid5000@IRIT, Overview and demo of Grid5000 platform: from CPU/GPU/ARM/… computing to low-level experimentation slides and material 2022 8 Dec 2022 Agrégation d’informatique slides présentation aux licence et master de l’Université Toulouse 3 17 Nov 2022 Numérique et changement climatique slides présentation pendant la soirée La transition numérique : quels enjeux pour demain ?

Publications/Code

Recent publications (2020 and later) are in my CV HAL page or directly in my HAL page Older publications (up to 2020) are in the IRIT publication database Most publication are available through Google Scholar Another way to access them is through DBLP One other way is to use ResearchGate Code MojitO/S: An open source system, energy and network monitoring tool at the O/S level Expetator: A tool for running HPC applications using several type of leverages (DVFS) and low-level monitoring (hardware performance counters, RAPL)

Committees

You can find here the events in which I participated in the organization, the ones I was in the steering committee, the link on the list of my journal reviews, and the list of the TPCs in which I participated. Event organization I organized the following events: Autonomic Computing, Datacenters and Cyberinfrastructure track chair at CCGRID 2019 GreenDays@Toulouse 2018 July 2 and 3 2018: From IoT to Exascale, where are we on advances on energy efficiency and Co2 emissions reduction ?

Energy and performance monitoring and models for Exascale computing

Context High Performance Computing usage is growing from climate science studies to chemical research. The increased impact of these computation opens the field of research on how to manage and reduce their energy consumption. In the NumPEx project we aim at developing state-of-the-art skills and infrastructures in the field of exascale computing. One of the pillars of NumPEx focuses on making exascale computing sustainable. To make informed cluster-level scheduling decisions and to provide feedback to users, information on the whole infrastructure is needed.

Internship/project position: Real-time distributed system (hardware performance counters, RAPL, ...) monitoring for HPC

Context High Performance Computing usage is growing from climate science studies to chemical research. The increased impact of these computation opens the field of research on how to manage and reduce their energy consumption. In the NumPEx project we aim at developing state-of-the-art skills and infrastructures in the field of exascale computing. One of the pillars of NumPEx focuses on making exascale computing sustainable. To make informed cluster-level scheduling decisions and to provide feedback to users, information on the whole infrastructure is needed.

Internship/project position: Real-time phase detection for large-scale HPC applications

Context High Performance Computing usage is growing from climate science studies to chemical research. The increased impact of these computation opens the field of research on how to manage and reduce their energy consumption. In the NumPEx project we aim at developing state-of-the-art skills and infrastructures in the field of exascale computing. One of the pillars of NumPEx focuses on making exascale computing sustainable. To make informed cluster-level scheduling decisions and to provide feedback to users, information on the whole infrastructure is needed.

Internship/project position: Sustainable monitoring of large-scale HPC applications: Reducing data amount to save energy

Context High Performance Computing usage is growing from climate science studies to chemical research. The increased impact of these computation opens the field of research on how to manage and reduce their energy consumption. In the NumPEx project we aim at developing state-of-the-art skills and infrastructures in the field of exascale computing. One of the pillars of NumPEx focuses on making exascale computing sustainable. To make informed cluster-level scheduling decisions and to provide feedback to users, information on the whole infrastructure is needed.

Apprentissage par Bandits pour du DVFS efficace en énergie en contexte HPC

Contexte La consommation d’énergie des ordinateurs devient une préoccupation majeure dans le cadre du réchauffement climatique. Pour optimiser leur consommation électrique d’application informatique, il est nécessaire de disposer d’informations précises sur leur comportement. Il devient alors possible de choisir la bonne fréquence d’un processeur. Cependant, le choix de la vitesse de fréquence peut fortement détériorer son fonctionnement, ou au contraire, n’avoir aucun effet visible pour l’utilisateur. Objectif L’objectif de ce projet sera réalisé en plusieurs étapes

Monitoring des performances énergétiques programmation GPU

Encadrants Georges Da Costa, Loïc Barthe, Nicolas Mellado Contexte Ce stage s’inscrit dans les thématiques de recherche des équipes SEPIA et STORM de l’IRIT. L’équipe SEPIA s’intéresse à l’économie d’énergie dans les datacenters. En effet ces derniers sont constitués de plusieurs milliers d’ordinateurs et leur impact écologique les placent au niveau de l’industrie de l’aviation. Les travaux de l’équipe SEPIA se positionnent autant au niveau algorithmique (ordonnancement de tâches, reconfiguration d’applications) qu’au niveau des outils de support (lancement d’expériences sur plusieurs centaines de machines, monitoring bas niveau de performance et d’énergie).