May 19, 2022
Polaris-tt: Henry-Joseph Audeoud (title to be annouced)
Polaris-tt: Henry-Joseph Audeoud (title to be annouced)
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May 19, 2022
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News
- Journée au vert POLARIS 2022/05/23
- DATAMOVE/POLARIS picnic 2021/06/22
- DATAMOVE/POLARIS BBQ 2019 2019/06/14
- POLARIS Bootcamp (May 2019) 2019/05/24
- slides of Andras Gyorgy 2016/01/15
Next seminars
Events
Events in May–June 2022
MMonday TTuesday WWednesday TThursday FFriday SSaturday SSunday 25April 25, 202226April 26, 202227April 27, 2022Polaris-tt: Victor Leger – A large dimensional analysis of multi-task semi-supervised classification
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April 28, 2022Seminar by Martin Schreiber (LJK, Airsea)
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April 28, 2022Title: A Brief Glimpse on Emerging Time Integration Methods for Weather and Climate Simulations
Speaker: Martin Schreiber
Abstract:
Weather and climate simulations face new challenges due to changes in computer architectures caused by physical limitations. From a pure computing perspective, algorithms are required to cope with stagnating or even decreasing per-core speed and increasing on-chip parallelism. These trends will continue and already led to research on partly disruptive mathematical and algorithmic reformulations of dynamic cores, e.g., using (additional) parallelism along the time dimension.
This presentation provides an overview and introduction of a variety of promising newly developed and evaluated time integration methods for equations related to prototypical dynamical cores, all aimed at improving the ratio of wall clock time vs. error: Rational Approximation of Exponential Integration (REXI), Parallel Full Approximation Scheme in Space and Time (PFASST) and Semi-Lagrangian methods combined with Parareal. We get improved time-vs.-error rates, but sometimes with additional challenges on the way which needs to be further overcome. Overall, our results motivate further investigation and combination of these methods for operational weather/climate systems.
I gratefully acknowledge collaborators related to this presentation
Jed Brown, Finn Capelle, François Hamon, Terry Haut, Richard Loft, Michael Minion, Matthew Normile, Nathanael Schaeffer, Andreas Schmitt, Pedro S. Peixoto, Raphael Schilling29April 29, 202230April 30, 2022May
1May 1, 20222May 2, 20223May 3, 20224May 4, 2022Polaris-tt: Hugo Lebeau – A random matrix analysis of kernel-based online learning: coping with limited memory resources
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May 5, 2022Polaris-datamove Seminar: Jonatha Anselmi (Title: Recent advances in load balancing: replication, speculation and auto-scaling)
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May 5, 2022Title: Recent advances in load balancing: replication, speculation and auto-scalingAbstract: In this talk, we will discuss modern approaches for load balancing in large-scale parallel-server systems: replication, speculation and auto-scaling. Replication sends multiple copies of a given job, simultaneously upon its arrival, to multiple servers and then uses the results from whichever copy responds first. Speculation sends one or multiple copies of a given job only once the system smartly detects it as a "straggler", i.e., as a job taking longer than expected to complete because of some unfortunate runtime phenomenon. Auto-scaling allows the net service capacity, or overall number of servers, to scale up or down in response to the current load and within the same timescale of job dynamics. We will review the state of the art and present some recent results in the flavour of mean-field and fluid limit theorems.
6May 6, 20227May 7, 20228May 8, 20229May 9, 202210May 10, 202211May 11, 2022Workshop d'axe
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May 12, 202213May 13, 202214May 14, 202215May 15, 202216May 16, 202217May 17, 202218May 18, 2022Polaris-tt: Henry-Joseph Audeoud (title to be annouced)
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May 19, 202220May 20, 202221May 21, 202222May 22, 202223May 23, 202224May 24, 202225May 25, 202226May 26, 202227May 27, 202228May 28, 202229May 29, 202230May 30, 202231May 31, 2022June
1June 1, 2022Séminaire Michel Davydov: "Proving the Poisson Hypothesis for Replica-Mean-Field Models"
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June 2, 2022Title : Proving the Poisson Hypothesis for Replica-Mean-Field ModelsAbstract :
Modeling particles or agents as nodes of a network interacting over time is a common approach in a variety of fields. Unfortunately, most relevant dynamics involve complex graphs of interactions for which an exact computational treatment is impossible. To circumvent this difficulty, the replica-mean-field approach focuses on randomly interacting replicas of the networks of interest. In the limit of an infinite number of replicas, these networks become analytically tractable under the so-called Poisson Hypothesis, which postulates that replicas become asymptotically independent and arrivals to a given neuron become Poisson distributed. This hypothesis is often conjectured or numerically validated but not proven. We show the validity of the Poisson Hypothesis for large classes of processes that include for example Galves-Löcherbach models from computational neuroscience.3June 3, 20224June 4, 20225June 5, 20226June 6, 20227June 7, 20228June 8, 2022Polaris-datamove seminar: "Pierre Gaillard" (Inria). Title: Online portfolio selection
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June 9, 202210June 10, 202211June 11, 202212June 12, 2022These Vitalii Emelianov
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June 13, 202214June 14, 202215June 15, 2022Polaris-datamove seminar: Romain Couillet
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June 16, 202217June 17, 202218June 18, 202219June 19, 202220June 20, 202221June 21, 202222June 22, 202223June 23, 202224June 24, 202225June 25, 202226June 26, 202227June 27, 202228June 28, 202229June 29, 2022Polaris-tt: Dorian Buffière.
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June 30, 2022Conception de politiques d'auto-scaling pour les platformes "serverless"
Batiment IMAG (Room 306)July
1July 1, 20222July 2, 20223July 3, 2022Meta
