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).
List of talks, tutorials, and other presentations
2023 27 Nov 2023 Table ronde Repenser des infrastructures informatiques 5G et Cloud écoresponsables slides pendant la conférence les sciences informatiques écoresponsables organisée par CNRS Sciences informatiques
20 Oct 2023 Energy and environmental impact and sustainability slides during the InPEx Pre-workshop
25 and 26 Sep 2023 Science du numérique : Numérique et changement climatique slides
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.
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)
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 ?
Le présent sujet de stage s’inscrit dans le cadre du projet européen SLICES, dont l’objectif est la création d’une Infrastructure de Recherche (IR) pour le traitement numérique de la donnée, allant du capteur connecté (IoT) au traitement de données (Cloud), en passant par les protocoles réseau. Cette IR, en gestation, sera composée, entre autres, de nœuds comme ceux présents sur Toulouse, sur G5k [1] et LocURa4IoT [2].
L’objectif du stage est de proposer et expérimenter plusieurs scénarios illustrant cette IR.
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.
Context There is an increasing interest in a new distributed ML paradigm called Federated Learning (FL)[La17], in which nodes compute their local gradients and communicate them to a central server. This centralized server then orchestrates rounds of training over large data volumes created and stored locally at a large number of nodes. This training procedure repeats until some criterion are met. This enables the participating nodes (e.g., IoT devices, mobile phones, etc) to protect their data and solve the data security and privacy issues imposed by law.
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.
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.
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.
