May 7, 2020
keynote LIG
keynote LIG
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May 7, 2020
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News
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- slides of Andras Gyorgy 2016/01/15
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- 2:00 pm – 3:00 pm, April 30, 2024 – Seminar Rémi Castera
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Events in May–June 2020
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1May 1, 20202May 2, 20203May 3, 20204May 4, 20205May 5, 20206May 6, 2020keynote LIG
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May 7, 20208May 8, 20209May 9, 202010May 10, 202011May 11, 202012May 12, 202013May 13, 202014May 14, 202015May 15, 202016May 16, 202017May 17, 202018May 18, 202019May 19, 202020May 20, 202021May 21, 202022May 22, 202023May 23, 202024May 24, 202025May 25, 202026May 26, 202027May 27, 202028May 28, 202029May 29, 202030May 30, 202031May 31, 2020June
1June 1, 20202June 2, 20203June 3, 20204June 4, 20205June 5, 20206June 6, 20207June 7, 20208June 8, 20209June 9, 202010June 10, 2020Aurélien Garivier (Postponed due to COVID lockdown)
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June 11, 2020TBA
Bâtiment IMAG (442)12June 12, 202013June 13, 202014June 14, 202015June 15, 2020Stéphan Plassart [PhD defense]: Online Energy Optimization for real-time systems
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June 16, 2020I have the pleasure to announce you my PhD defense, entitled « Online Energy Optimization for real-time systems », which will be held by video-conference.
The members of the jury are:
- Sara Alouf, Researcher hdr, Inria Sophia Antipolis - Méditerranée center, Examinatrice.
- Nathalie Bertrand, Researcher hdr, Inria Rennes-Bretagne Atlantique center, Examinatrice.
- Liliana Cucu-grosjean, Researcher hdr, Inria Paris center, Rapporteure.
- Bruno Gaujal, Research Director, Inria Grenoble Rhône-alpes center, Directeur de thèse.
- Jean-philippe Gayon, Professor, Clermont Auvergne University, Rapporteur.
- Alain Girault, Research Director, Inria Grenoble Rhône-alpes center, Directeur de thèse.
- Florence Maraninchi, Professor, Grenoble-INP, Examinatrice.
- Isabelle Puaut, Professor, Rennes 1 University, Examinatrice.
Abstract: The energy consumption is a crucial issue for real-time systems, that's why optimizing it online, i.e. while the processor is running, has become essential and will be the goal of this thesis. This optimization is done by adapting the processor speed during the job execution. This thesis addresses several situations with different knowledge on past, active and future job characteristics. Firstly, we consider that all job characteristics are known (the offline case), and we propose a linear time algorithm to determine the speed schedule to execute n jobs on a single processor. Secondly, using Markov decision processes, we solve the case where past and active job characteristics are entirely known, and for future jobs only the probability distribution of the jobs characteristics (arrival times, execution times and deadlines) are known. Thirdly we study a more general case: the execution is only discovered when the job is completed. In addition we also consider the case where we have no statistical knowledge on jobs, so we have to use learning methods to determine the optimal processor speeds online. Finally, we propose a feasibility analysis (the processor ability to execute all jobs before its deadline when it works always at maximal speed) of several classical online policies, and we show that our dynamic programming algorithm is also the best in terms of feasibility.
17June 17, 2020Giorgio Fabbri (GAEL)
19June 19, 202020June 20, 202021June 21, 202022June 22, 202023June 23, 202024June 24, 2020PhD defense Dong Quan Vu
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June 25, 202026June 26, 202027June 27, 202028June 28, 202029June 29, 202030June 30, 2020July
1July 1, 2020Seminar: Salah Zrigui
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July 2, 2020Title: Classification of energy profiles of HPC tasks
Abstract: Salah will present how he analyzed, characterized and tried to classify energy consumption traces (time series) of HPC codes running on one of the GRICAD cluster.
3July 3, 20204July 4, 20205July 5, 2020Meta
