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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 2018
MMonday TTuesday WWednesday TThursday FFriday SSaturday SSunday 30April 30, 2018May
1May 1, 20182May 2, 20183May 3, 2018A data structure for analyzing spatio-temporal correlations of alarms, by Anne Bouillard (Nokia)
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May 4, 2018In this talk, I will present a data structure for the analysis of correlations of alarms, for root-cause analysis or prediction purposes. This is a joint work with Marc-Olivier Buob and Maxime Raynal (intern). A sequence of alarms is modeled by a directed acyclic graph. The nodes of the graph are the alarms, that are represented by a symbol and an interval of time. An arc of the graph is interpreted as a potential causality between two alarms. I will first show how to build a "compact" structure storing all the potential causal sequences of alarms and then how to weight this structure so that the actual correlations can be detected. The efficiency of the approach will be demonstrated on toy examples.
Bâtiment IMAG (442)5May 5, 20186May 6, 20187May 7, 20188May 8, 20189May 9, 201810May 10, 201811May 11, 201812May 12, 201813May 13, 201814May 14, 201815May 15, 201816May 16, 201817May 17, 201818May 18, 201819May 19, 201820May 20, 201821May 21, 201822May 22, 201823May 23, 201824May 24, 201825May 25, 201826May 26, 201827May 27, 201828May 28, 201829May 29, 201830May 30, 2018Analytical Modeling for Flow-level Performance of Randomly Placed Wireless Networks by George Arvanitakis (postdoc, Polaris)
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May 31, 2018The recent evolution of mobile communications and the widespread use of ``smart'' mobile devices have radically changed the behavior and the needs of the mobile user. In the developed world, people that use their mobile devices just to place some calls and to text some SMS can be characterized as endangered species. Ubiquitous access to Internet, videos/songs streaming and upload/download data flows on the fly are some of the modern demands of the mobile user. It would not be an exaggeration to say that modern users have almost the same demands regardless if they are connected through wire to the network from their personal computers or if they have established a wireless connection through their cellular devices.
On the one hand the overall network load increases on the other hand base stations have limited resources due to the fact that are able to operate only to a limited part of the electromagnetic spectrum. Some (temporal) solutions for the aforementioned problem are the expansion of frequency operational bands (mm wave) or the use of more antennas (massive MIMO) or the denser deployment of small cells. In this talk, we are interested in the promising case of denser small cells that will be tighter integrated with the macro cell. Unfortunately to deploy optimally a small cell network is not trivial. A small cell network is usually deployed in an ad-hoc style and not all at once, so a part of the network exists already and cannot be planned. Additionally, there are natural obstacles and physical limitations that do not allow to deploy base stations wherever we want. So, the small cell network's topology is quite different from the traditional (macro cell) well-structure one.
From our point of view, the future of mobile communications will approach the following: A mass of users - will cause a nondescript data traffic - that will be served from an irregular planed and heterogeneous network. This chaotic picture however makes the problem of network modeling and performance analysis extremely challenging.
To this end, the our primary focus is to build up an analytical framework in order to analyze the performance of a randomly placed network, which serves randomly placed users. To achieve this, we based our analysis on two main tools: (a) stochastic geometry, to understand the impact of topological randomness and coverage maps and (b) queueing theory, to model the competition between concurrent flows within the same BS. The second goal is to propose, based on this analysis, some general design guidelines and insights about specific communication scenarios that mainly involve LTE and WiFi networks.
Bat. IMAG, 206June
1June 1, 20182June 2, 20183June 3, 20184June 4, 20185June 5, 20186June 6, 2018Keynote du LIG: Erol Gelenbe
8June 8, 20189June 9, 201810June 10, 201811June 11, 201812June 12, 201813June 13, 2018Towards a control-theory approach for minimizing unused grid resources, by Agustín Yabo (Master 2, Datamove + Ctrl-A)
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June 14, 2018HPC systems are facing more and more variability in their behavior, related to e.g., performance and power consumption, and the fact that they are less predictable requires more runtime management. This can be done in an Autonomic Management feedback loop, in response to monitored information in the systems, by analysis of this data and utilization of the results in order to activate appropriate system-level or application-level feedback mechanisms (e.g., informing schedulers, down-clocking CPUs).
Such problem is found in the context of CiGri, a simple, lightweight, scalable and fault tolerant grid system which exploits the unused resources of a set of computing clusters. Computing power left over by the execution of a main HPC application scheduling is used to execute smaller jobs, which are injected as much as the global system allows.
The seminar will presents results addressing the problem of automated resource management in an HPC infrastructure, using techniques from Control Theory to design a controller that maximizes cluster utilization while considering cluster and fileserver overloading. We draw from a previous work where a proportional-integral feedback (Proportional Integral, PI) control loop was implemented, through a maximum number of jobs to be sent to the cluster, in response to system information about the current number of jobs processed. Then, we proposed a dynamical model for the system queue, cluster and fileserver load with time-varying parameters, an EKF (Extended Kalman Filter) for performing online parameter estimation and an MPC (Model-Predictive Control) approach for regulating the desired values of the infrastracture to the desired ones.Bat. IMAG, 20615June 15, 201816June 16, 201817June 17, 201818June 18, 201819June 19, 201820June 20, 2018Pré-soutenances M2R DATAMOVE/POLARIS
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June 21, 2018- Emelianov Vitalli
- Janon Alexis
- Colao Henrique
- Zuhlhusni Abdul
Bâtiment IMAG (206)A Flexible Distributed Optimization Scheme with Asynchronous, Scarse, and Sparse Communications, by Franck Iutzeler (LJK)
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June 21, 2018We present an asynchronous algorithm for distributed convex optimization when the objective writes a sum of smooth functions, local to each worker, and a non-smooth function. This kind of problem typically appears when learning over distributed data. Unlike many existing methods, our algorithm is adjustable to various levels of communication cost, delays, machines computational power. Moreover, for L1-regularized problems, this algorithm identifies near-optimal sparsity patterns and leverages on it to improve the efficiency of communications.
Bat. IMAG, 306Pré-soutenances M2R DATAMOVE/POLARIS
Pré-soutenance de thèse de Benoit Vinot
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June 22, 2018Conception d'un système d'information distribué pour la conduite des flexibilités dans un réseau de distribution électrique: modélisation, simulation et implémentation
Résumé français :
Le secteur industriel de l'énergie, et les réseaux électriques en particulier, rendent à nos sociétés modernes d'immenses services dont nous ne pouvons plus nous passer. Ils présentent aussi, hélas, un certain nombre de graves inconvénients, notamment en matière d'impact environnemental. Ces inconvénients apparaissent aujourd'hui comme inacceptables; le secteur de l'énergie s'efforce donc actuellement de les amoindrir autant que possible, dans le cadre de ce qu'on appelle la transition énergétique.
Outre d'indispensables efforts en matière de sobriété et d'efficacité énergétique, deux grands axes d'amélioration se dessinent: d'une part, le remplacement progressif de certains moyens de production
d'électricité conventionnels par des moyens de production renouvelables; et d'autre part, le transfert de certains usages aujourd'hui non-électriques vers l'électricité --- en particulier en matière de mobilité.L'intégration au réseau électrique de ces nouveaux types de dispositifs pose cependant des difficultés techniques considérables, qui motivent depuis le début des années 2000 de nombreux travaux sur le thème de ce que l'on appelle aujourd'hui les "smart grids": des réseaux électriques compatibles avec les exigences de
la transition énergétique, c'est-à-dire capables d'accueillir massivement les nouveaux types d'usages comme la production photovoltaïque et les bornes de recharge des véhicules électriques, ceci
notamment grâce à l'utilisation accrue des nouvelles technologies de l'information et de la communication.Parmi les difficultés susmentionnées, qui limitent la capacité d'accueil du réseau, figurent les congestions, c'est-à-dire les limites physiques à la puissance que l'on peut faire transiter d'un point à un autre sur une infrastructure donnée. C'est à la gestion des congestions que nos travaux sont consacrés. À ce sujet, la question
fondamentale est de déterminer par quel enchaînement de mesures, de calcul, de communications et in fine d'actions, on peut passer d'une situation de contrainte sur un réseau de distribution d'électricité, à une situation où cette contrainte a été éliminée par l'action des flexibilités environnantes; autrement dit, en augmentant ou en réduisant judicieusement la production et/ou la consommation locales, et éventuellement en jouant sur d'autres types de leviers.L'objet de cette thèse est de participer à l'élaboration des outils conceptuels et informatiques qui nous permettront de répondre à la question fondamentale ci-dessus. Nos travaux portent ainsi sur la question de la modélisation des réseaux de distribution d'électricité "flexibles", et sur l'implémentation concrète des modèles retenus sous forme d'un logiciel de simulation ad hoc, parfaitement adapté à l'étude de ce type de réseaux.
Abstract :
The energy sector and the electrical networks in particular, provide great and indispensable services to our modern societies. Unfortunately, they also bring some serious drawbacks, especially with regard to the environment. These drawbacks are becoming more and more unacceptable; that is why the energy sector is
trying to reduce them as much as possible, in the framework of the so-called energy transition.In addition to mandatory efforts in terms of energy efficiency and sobriety, two major directions of improvement have been identified: on the one hand, the progressive replacement of some conventional power plants with renewable production units; and on the other hand, the transfer of several non-electrical usages towards electricity --- in particular in the area of mobility.
The integration of these new devices into electrical networks raise new technical challenges which, since the early 2000s, have been driving a lot of work about so-called "smart grids": electrical networks compatible with the requirements of the energy transition, ie. able to host new devices like photovoltaic solar panels and charging stations for electric vehicles, notably through the increasing usage of new information and communications technologies.
Among the difficulties mentioned above, which limit the hosting capacity of the network, there are congestions ie physical constraints limiting the amount of power that may be transmitted through a given infrastructure. Our work is devoted to the management of congestions. The fundamental issue thereon is to define a sequence of decisions, computations, communications and in fine actions that allows to move from a constrained situation on the electrical distribution network, to a situation in which the action of local flexibilities has lifted the constraint; in other words, to a situation where increasing or decreasing local generation and/or consumption, or taking some other control action, relieved the network.
The aim of this thesis is to contribute to the development of conceptual and computing tools that will allow us to answer the fundamental aforementioned issue. Our work thus deals with the modelling of flexible electrical distribution networks, and with the tangible implementation of selected models in the form of
ad hoc simulation software, specifically designed for the study of such networks.Bâtiment IMAGSaint-Martin-d'Hères, 38400France23June 23, 201824June 24, 201825June 25, 201826June 26, 201827June 27, 2018Real-Time Scheduling Policy Selection using Machine Learning by Raphael Camargo(Sao Paulo)
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June 28, 2018We present a real-time scheduling policy selection algorithm, which takes as input the running queue job characteristics and machine states. We evaluated the use of logistic regression and support vector machines to perform the mapping from queue and machine state to selected scheduling policy. The machine learning algorithms are trained and evaluated using simulations configured using HPC platform traces. When selecting among 5 (five) scheduling policies and using SVM with polynomial kernel, we obtained an accuracy above 80%, when compared to the best possible selection. When simulating the online real-time selection of policies for a period of one year, the method had a performance between selecting the best possible selection of policies and random selection, when considering the mean queue waiting time.
Bâtiment IMAG (206)29June 29, 201830June 30, 2018July
1July 1, 2018Meta
Performance evaluation and Optimization of LARge Infrastructures and Systems
