Cosmological Simulations on a Grid of Computers

The work presented in this paper aims at restricting the input parameter values of the semi-analytical model used in GALICS and MOMAF, so as to derive which parameters influence the most the results, e.g., star formation, feedback and halo recycling efficiencies, etc. Our approach is to proceed empirically: we run lots of simulations and derive the correct ranges of values. The computation time needed is so large, that we need to run on a grid of computers. Hence, we model GALICS and MOMAF execution time and output files size, and run the simulation using a grid middleware: DIET. All the complexity of accessing resources, scheduling simulations and managing data is harnessed by DIET and hidden behind a web portal accessible to the users.Comment: Accepted and Published in AIP Conference Proceedings 1241, 2010, pages 816-82

Efficient Grid Resource Selection for a CEM Application

National audienceComputational Electromagnetics (CEM) is a domain which provides numerical solutions to compute an- tenna performance, electromagnetic compatibility, radar cross section and electromagnetic wave propaga- tion. The ever-increasing need for more precision and larger meshes raises the natural question whether it is worth porting CEM algorithms to computer grids. Due to the nature of the computations, CEM al- gorithms are not trivially parallelisable, as data dependency inside the mesh implies communication. The goal of this paper is to answer the question: given a set of resources, what is the subset of resources one should chose among, to minimise the time it takes to solve a CEM problem. After presenting a model of the application execution time, several algorithms for selecting resources are described. The limits of the theoretical model is then compared against experimental results, obtained from the Grid'5000 platform

A Practical Study of Self-Stabilization for Prefix-Tree Based Overlay Networks

Service discovery is crucial in the development of fully decentralized computational grids. Among the significant amount of work produced by the convergence of peer-to-peer (P2P) systems and grids, a new kind of overlay networks, based on prefix trees, has emerged. In particular, the Distributed Lexicographic Placement Table (DLPT) approach is a decentralized and dynamic service discovery service. Fault-tolerance within the DLPT approach is achieved through best-effort policies relying on formal self-stabilization results. Self-stabilization means that the tree can become transiently inconsistent, but is guaranteed to autonomously converge to a correct topology after arbitrary crashes, in a finite time. However, during convergence, the tree may not be able to process queries correctly. In this paper, we present some simulation results having several objectives. First, we investigate the interest of self-stabilization for such architectures. Second, we explore, still based on simulation, a simple Time-To-Live policy to avoid useless processing during convergence time

Forecasting for Cloud computing on-demand resources based on pattern matching

The Cloud phenomenon brings along the cost-saving benefit of dynamic scaling. Knowledge in advance is necessary as the virtual resources that Cloud computing uses have a setup time that is not negligible. We propose a new approach to the problem of workload prediction based on identifying similar past occurrences to the current short-term workload history. We present in detail the auto-scaling algorithm that uses the above approach as well as experimental results by using real-world data and an overall evaluation of this approach, its potential and usefulness

Efficiency of Tree-Structured Peer-to-Peer Service Discovery Systems

The efficiency of service discovery is a crucial point in the development of fully decentralized middlewares intended to manage large scale computational grids. The work conducted on this issue led to the design of many peer-to-peer fashioned approaches. More specifically, the need for flexibility and complexity in the service discovery has seen the emergence of a new kind of overlays, based on tries, also known as lexicographic trees. Although these overlays are efficient and well designed, they require a costly maintenance and do not accurately take into account the heterogeneity of nodes and the changing popularity of the services requested by users. In this paper, we focus on reducing the cost of the maintenance of a particular architecture, based on a dynamic prefix tree, while enhancing it with some load balancing techniques that dynamically adapt the load of the nodes in order to maximize the throughput of the system. The algorithms developed couple a self-organizing prefix tree overlay with load balancing techniques inspired by similar previous works undertaken for distributed hash tables. After some simulation results showing how our load balancing heuristics perform in such an overlay and compare to other heuristics, we provide a fair comparison of this architecture and similar overlays recently proposed.L’efficacité de la découverte de services est un point crucial du développement d’intergiciels de grille totalement décentralisés. Les travaux ayant pour but la résolution de ce problème ont généré un certain nombre d’approches pair-à-pair. le besoin de flexibilité et d’expressivité a donné lieu au développement d’architecture s’appuyant sur des arbres de préfixes(ou arbres lexicographiques). Ces overlays souffrent d’une maintenance couteuse et ne prennent pas en compte la nature hétérogène de la plate-forme physique sous-jacente et la popularité différente et changeante de chaque ressource enregistrée.Dans ce rapport, nous nous focalisons sur la réduction du cout de maintenance d’une telle architecture, basée sur un arbre de préfixes dynamique,tout en lui donnant la possibilité de s’adapter à l’hétérogénéité précitée par l’enrichissant de mécanismes de répartition de la charge qui adaptent dynamiquement la charge des nœuds dans le but de maximiser le débit sur service. Notre approche couple des travaux de répartition de la charge dans les DHTs avec un overlay en arbre de préfixes auto-organisant. Après des résultats de simulation mettant en évidence l’efficacité de notre heuristique, nous comparons notre approche avec les travaux s’appuyant sur des structures distribuées similaires

Service discovery in a peer-to-peer environment for computational grids

Les grilles de calcul sont des systèmes distribués dont l'objectif est l'agrégation et le partage de ressources hétérogènes géographiquement réparties pour le calcul haute performance. Les services d'une grille sont l'ensemble des applicatifs que des serveurs mettent à disposition des clients. Une problématique largement soulevée par les utilisateurs de grilles est la découverte de services. Les mécanismes actuels de découverte de services manquent de fonctionnalités et deviennent inefficaces dans des environnements dynamiques à large échelle. Il est donc indispensable de proposer de nouveaux outils pour de tels environnements. Les technologies pair-à-pair émergentes fournissent des algorithmes permettant une décentralisation totale de la construction et de la maintenance de systèmes distribués performants et tolérants aux pannes. Le problème que l'on cherche à résoudre est de permettre une découverte flexible (recherche multicritères, complétion automatique) des services dans des grilles prenant place dans un environnement dynamique à large échelle (pair-à-pair) en tenant compte de la topologie du réseau physique sous-jacent

All in one Graphical Tool for the management of DIET a GridRPC Middleware

Also available as LIP Research Report 2008-24Grid Middleware are the link between large scale (and distributed) platforms and applications. Managing such a software system and the Grid environment itself can be a hard task when no dedicated (and integrated) tool exist. Some can be used through nice graphical interfaces, but they are usually dedicated to one or some limited tasks. They do not fulfill all the needs of a Grid end-user who wants to deploy Grid applications easily and rapidly. The aim of this paper is to present the case study of an all-in-one software system, designed for the management of a Grid Middleware and gathering user-friendly graphical interfaces answering to the various needs of end-users. Moreover the software system eases the use of the Grid by avoiding the scripting layer under a nice GUI enabling the user a faster and more efficient use of the Grid environment. By this means we demonstrate how the DietDashboard fulfills all the needs of a unified tool for Grid management. This paper gives a comparison with existing and well-known tools dedicated to some specific tasks such as Grid resources management, Grid monitoring, or Middleware management

Modelization for the Deployment of a Hierarchical Middleware on a Homogeneous Platform

Accessing the power of distributed resources can nowadays easily be done using a middleware based on a client/server approach. Several architectures exist for those middlewares. The most scalable ones rely on a hierarchical design. Determining the best shape for the hierarchy, the one giving the best throughput of services, is not an easy task. We first propose a computation and communication model for such hierarchical middleware. Our model takes into account the deployment of several services in the hierarchy. Then, based on this model, we propose an algorithm for automatically constructing a hierarchy. This algorithm aims at offering the users the best obtained to requested throughput ratio, while providing fairness on this ratio for the different kind of services, and using as few resources as possible. Finally, we compare our model with experimental results on a real middleware called DIET

Autonomic Management using Self-Stabilization for Hierarchical and Distributed Middleware

International audienceDynamic nature of distributed architecture is a major challenge to avail the benefits of distributed computing. An effective solution to deal with this dynamic nature is to implement a self-adaptive mechanism to sustain the distributed architecture. Self-adaptive systems can autonomously modify their behavior at run-time in response to changes in their environment. This capability may be included in the software systems at design time or later by external mechanisms. Our paper describes the self- adaptive algorithm that we developed for an existing middleware. Once the middleware is deployed, it can detect a set of events which indicate an unstable deployment state. When an event is detected, some instructions are executed to handle the event. We have designed a simulator to have a deeper insights of our proposed self-adaptive algorithm. Results of our simulated experiments validate the safe convergence of the algorithm

Gestion adaptative de l'énergie pour les infrastructures de type grappe ou nuage

National audienceDans un contexte d'utilisation de ressources hétérogènes, la performance reste le critère traditionnel pour la planification de capacité. Mais, de nos jours, tenir compte de la variable énergétique est devenu une nécessité. Cet article s'attaque au problème de l'efficacité énergétique pour la répartition de charge dans les systèmes distribués. Nous proposons une gestion efficace en énergie des ressources par l'ajout de fonctionnalités de gestion des évènements liés à l'énergie, selon des règles définies par l'utilisateur. Nous implémentons ces fonctionnalités au sein de l'intergiciel DIET, qui permet de gérer la répartition de charge afin de mettre en évidence le cout des compromis entre la performance et la consommation d'énergie. Notre solution et son intérêt sont validés au travers d'expériences en évaluant la performance et la consommation électrique mettant en concurrence trois politiques d'ordonnancement. Nous mettons en avant le gain obtenu en terme énergétique tout en essayant de minimiser les écarts de performance. Nous offrons également à l'intergiciel responsable de l'ordonnancement une réactivité face aux variations énergétiques