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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 October–November 2022
MMonday TTuesday WWednesday TThursday FFriday SSaturday SSunday 26September 26, 202227September 27, 202228September 28, 202229September 29, 202230September 30, 2022October
1October 1, 20222October 2, 20223October 3, 20224October 4, 20225October 5, 20226October 6, 20227October 7, 20228October 8, 20229October 9, 202210October 10, 202211October 11, 2022Seminar Joao Comba: Data Visualization for The Understanding of COVID-19
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October 12, 2022Title: Data Visualization for The Understanding of COVID-19
Speaker: Joao Comba (UFRGS)
Abstract: In this talk, I will describe several data visualization
projects related to COVID-19 data analysis. The first work describes
an analysis tool for comparing the evolution of COVID-19
data in different regions worldwide. The main component of our tool is
a similarity engine that searches for similar patterns of COVID-19 time
series and a storytelling dashboard that identifies the waves of COVID-
19. We also introduce a new type of difference plot that allows a more
straightforward comparison of time series evolution. The second work
leverages the big-data infrastructure we developed for real-time
analysis to study two years of clinical admissions in the public health
system of Brazil, composed of more than 100 million records. The third
work is related to the diagnosis of COVID-19 from computed tomography
and clinical data. We will describe COVID-VR, a novel approach for
classifying pulmonary diseases based on volume rendering images of the
lungs taken from different angles, thus providing a global view of the
entire lung in each image. I will conclude the talk with a summary of
my current research projects.
Short-bio: João L. D. Comba is a Full Professor at the Instituto de
Informática at UFRGS, where he conducts research activities,
undergraduate and graduate education, and supervises doctoral,
master, and scientific initiation students. He holds a Ph.D. in
Computer Science from Stanford University, United States. 2000. His
research areas include data visualization and analysis, data science,
geometric algorithms, and spatial data structures. He is currently co-
chair of the Visualization Corner of the Journal Computing in Science &
Engineering and associate editor of the Computer & Graphics Journal.Bâtiment IMAG (442)Séminaire Antoine Oustry: Polynomial optimization for parameterizing dynamical systems
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October 13, 2022Polynomial optimization for parameterizing dynamical systems
Abstract: We consider a polynomial dynamical system that depends on some tunable parameters. We raise the question of how to configure this system optimally, in terms of costs and stability.
More precisely, we will give an overview of polynomial optimization approaches to
(a) find a (stable) equilibrium point of the dynamical system that minimizes a polynomial function
(b) approximate regions of stability around the equilibrium points.
We illustrate our work with some applications in power engineering.14October 14, 202215October 15, 202216October 16, 202217October 17, 202218October 18, 202219October 19, 2022Séminaire Philippe Swartvagher (Inria Bordeaux): Possible interactions between task-based runtime systems and communication libraries
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October 20, 2022Titre : Possible interactions between task-based runtime systems and communication libraries
Abstract :
The increasing complexity of supercomputers leads to the emergence of task-based runtime systems, to exploit more easily the performance they can offer. These runtime systems usually rely on a third-party library to perform communications (following the MPI standard, for instance) when they are used in a distributed fashion. In this presentation, I will summarize my work during my PhD about possible interactions between task-based runtime systems and communication libraries. The interactions can be positive, for instance improving the performance by detecting and executing broadcasts in a smart way; or negative and hurting the application performance, for instance because of contention between communications and computations. I will also mention some results regarding the tracing system used to analyze executions: the sources of overhead and the problem of accurate clock synchronization.
21October 21, 202222October 22, 202223October 23, 202224October 24, 202225October 25, 202226October 26, 2022Seminar Bryce Ferguson: "Information and Influence: Overcoming and Exploiting Uncertainty in Congestion Games"
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October 27, 2022Bryce Ferguson (https://web.ece.ucsb.edu/~blf/)Title: Information and Influence: Overcoming and Exploiting Uncertainty in Congestion GamesAbstract: In large-scale, socio-technical systems (such as traffic networks, power grids, supply chains, etc.) the operating efficiency depends heavily on the actions of human users. It is well known that when users act in their own self-interest, system performance can be sub-optimal. Our capabilities in alleviating this inefficiency rely on our knowledge of user decision making and various system parameters. In this talk, I will present two settings where information affects our ability to influence system performance. In the first, we consider designing monetary incentives for players in a congestion game without exact knowledge of users’ price-sensitivity or path latency-characteristics; we provide a comparison of the effectiveness of different incentive types and quantify the value of different pieces of information. In the second, we consider a flipped paradigm, where the system operator has more information about system parameters than the users and can selectively reveal pertinent information. We show, in the context of Bayesian-congestion games, that signaling information to users has the opportunity to improve system performance but also the capability to make performance worse than if no information were shared at all. We then show the advantages of concurrently using monetary incentives and information signals by providing bounds on the benefit to system performance and methods to find optimal mechanisms of each type.Bâtiment IMAG (406)Saint-Martin-d'Hères, 38400France28October 28, 202229October 29, 202230October 30, 202231October 31, 2022November
1November 1, 20222November 2, 20223November 3, 20224November 4, 20225November 5, 20226November 6, 20227November 7, 20228November 8, 20229November 9, 2022Verimag seminar: Stephan Plassart
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November 10, 2022Total Flow Analysis (TFA) is a method for conducting the worst-case analysis of time sensitive networks without cyclic dependencies. In networks with cyclic dependencies, Fixed-Point TFA introduces artificial cuts, analyses the resulting cycle-free network with TFA, and iterates. If it converges, it does provide valid performance bounds. We show that the choice of the specific cuts used by Fixed-Point TFA does not affect its convergence nor the obtained performance bounds, and that it can be replaced by an alternative algorithm that does not use any cut at all, while still applying to cyclic dependencies.
Room: 206
Bâtiment IMAG (206)11November 11, 202212November 12, 202213November 13, 202214November 14, 202215November 15, 202216November 16, 2022Seminar Olivier Bilenne
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November 17, 2022Solutions of Poisson's equation for first-policy improvement in parallel queueing systemsThis talk addresses the problem of (state-aware) job dispatching at minimum long-run average cost in a parallel queueing system with Poisson arrivals. Policy iteration is a technique for approaching optimality through improvement of an initial dispatching policy. Its implementation rests on the computation of value functions. In this context, we will consider the M/G/1-FCFS queue endowed with an arbitrary cost function for the waiting times of the incoming jobs. The associated relative value function is a solution of Poisson's equation for Markov chains, which I propose to solve in the Laplace transform domain by considering an ancillary stochastic process extended to (imaginary) negative backlog states. This construction enables us to issue closed-form solutions for simple cost functions (polynomial, exponential, and their piecewise compositions), in turn permitting the derivation of interval bounds for the relative value functions to more general cost functions. Such bounds allow for an exact implementation of the first improvement step of policy iteration in a parallel queueing system.One objective of the talk is to identify the main obstacles to the implementation of the policy iteration algorithm in parallel queueing systems; the purpose then to discuss the new directions that transform domain analysis might offer beyond first policy improvement.Further reading: Olivier Bilenne. Dispatching to parallel servers: solutions of Poisson's equation for first-policy improvement. Queueing Systems, Springer Verlag, 2021, Queueing Systems, 99 (3), pp.199-230. https://hal.archives-ouvertes.fr/hal-0292528418November 18, 202219November 19, 202220November 20, 202221November 21, 202222November 22, 202223November 23, 202224November 24, 202225November 25, 202226November 26, 202227November 27, 202228November 28, 202229November 29, 202230November 30, 2022December
1December 1, 2022●(1 event)Séminaire Stephane Durand
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December 1, 2022Jeux de contagions et d'influences: les différentes formes, les approches et le contexte
2December 2, 20223December 3, 20224December 4, 2022Meta