Search

International audience; With a turnover of more than 4.2 billion euros in 2020 and a 20% share in the value of the French wine industry's exports, the champagne industry represents a considerable weight in the French economy. In this context of significant economic development, the issue of climate change has been added, calling into question the practices and means of production of the sector. The challenges related to global warming and an ever-increasing demand for yield can be addressed using the Internet of Things (IoT) and Artificial Intelligence (AI) technologies to benefit champagne production and answer these challenges. This article presents a solution to optimise Vranken Pommery products' quality and make environmentally friendly decisions by using intelligent sensors distributed as close as possible to the production and storage facilities to collect data. These sensors use LoRaWAN technology and protocol to communicate. The system integrates components capable of hosting artificial intelligence algorithms and using advanced microcontrollers that allow for intelligent communication network implementation while reducing power consumption and deployment costs.

International audience; The quality of the harvest depends significantly on the quality of the grapes. Therefore, winemakers need to make the right decisions to obtain highquality grapes. One of the first problems is estimating the yield of the crops. It allows winemakers to respect the specific norms of their appellation (yield quota, alcohol levels, etc.). It is also necessary to organise the logistics of the harvest (start date, human resources required, transportations, etc.). Traditionally, the yield estimation is performed by collecting grapes and berries over small, randomised samples, a destructive and laborious task. This work explores how automatic data acquisition combined with artificial intelligence can drive an automated and non-destructive yield estimation, adapted to the characteristics of each vine parcel.

International audience; Often, buzzwords like cloud, big data and IoT delight our imagination with the promise of eye-blink solutions for large-scale problems, the marvels of worldwide cloud infrastructures or the peak performance of the most recent TOP500 clusters. In practice, most of the times we have to face small to middle-size problems that require more than a computer to be solved in a satisfactory time but do not require always the use of top HPC infrastructures. In this talk we will discuss some aspects of fog/edge computing that, associated with green IT efforts, may help reducing costs and improve the use of existing resources around us.

National audience; Avec la dissémination des dispositifs portables (smart-phones, tablets, nano-ordinateurs, etc.) et leur augmentation en puissance de calcul, il est devenu essentiel de mettre en place une plate-forme pour la coordination des dispositifs et la gestion de leurs informations. Afin de garantir l'efficacité et le passageà l'échelle dans des environnements tels que l'Internet of Things (IoT), nous devons repenser les straté-gies de transmission et d'analyse des données de manièreà eviter la centralisation des ressources de stockage et de trai-tement. Dans ce travail, nous présentons des directions pour le développement de plates-formes pervasives multi-échelles, capables de mieux exploiter les ressources et les capacités de ces dispositifs afin d'offrir une meilleure qualité de service aux applications.

International audience; Molecular docking are widely used computational technics that allow studying structure-based interactions complexes between biological objects at the molecular scale. The purpose of the current work is to develop a framework that allows performing inverse virtual screening to test at a large scale a chemical ligand docking on a large dataset of proteins, which has several applications in the field of drug research. We developed different strategies to distribute the docking procedure, as a way to efficiently exploit the computational performance of multi-core and multi-machine (cluster) environments. This tool has been tested on 24 protein-ligand complexes taken from the Kellenberger dataset to show its ability to reproduce experimentally determined structures and binding affinities.

Deliverable 2.1; This document discusses the main requirements of a P2P computing middleware that satisfies the objectives of PER-MARE project. Starting with a comparison between MapReduce and FIIT paradigms, this document makes an inventory of the characteristics of CONFIIT, the P2P computing middleware initially aimed by the project. As CONFIIT does not respond to our needs, we establish the requirements for a new P2P tool that is being developed to replace CONFIIT. The main architectural elements of the new tool (called CloudFIT) are presented, as well as the details concerning its first prototype. Finally, we discuss the preliminary results obtained with this prototype, and set some development directions that shall guide the future research in the coming months.

International audience; MapReduce is a parallel programming paradigm successfully used to perform computations on massive amounts of data, being widely deployed on clusters, grid, and cloud infrastructures. Interestingly, while the emergence of cloud in- frastructures has opened new perspectives, several enterprises hesitate to put sensible data on the cloud and prefer to rely on internal resources. In this paper we introduce the PER- MARE initiative, which aims at proposing scalable techniques to support existent MapReduce data-intensive applications in the context of loosely coupled networks such as pervasive and desktop grids. By relying on the MapReduce programming model, PER-MARE proposes to explore the potential advan- tages of using free unused resources available at enterprises as pervasive grids, alone or in a hybrid environment. This paper presents the main lines that orient the PER-MARE approach and some preliminary results.

International audience; P2P computing middlewares are interesting options for grid computing applications that require scalability and resiliency. Nevertheless, most P2P computation systems rely on partially centralized or hybrid decentralized architectures to distribute tasks and collect the results, raising fault tolerance and bottleneck issues. CONFIIT (Computation Over Network with Finite number of Independent and Irregular Tasks) is a purely decentralized middleware for grid computing, relying on a virtual ring for topology management and for task scheduling. This paper evaluates the impact of node placement and task granularity on the performance of CONFIIT. We analyze how CONFIIT handles different distribution scenarios in a grid environment while solving the well-known Langford permutation problem.

International audience; Network security is in a daily evolving domain. Every day, new attacks, virus or intrusion techniques are released. Hence, network devices, enterprise servers or personal computers are potential targets of these attacks. Current secu- rity solutions like firewalls, intrusion detection systems (IDS) and virtual private networks (VPN) are centralized solutions which rely mostly on the analyze of inbound network connec- tions. This approach notably forgets the effects of a rogue station, whose communications cannot be easily controlled unless the administrators establish a global authentication policy using methods like 802.1x to control all network com- munications among each device. To the best of our knowledge, a distributed and easily manageable solution for the global security of an enterprise network does not exist. In this paper, we present a new approach to deploy a distributed security solution where communication between each device can be control in a collaborative manner. Indeed, each device has its own security rules, who can be shared and improved through exchanges with others devices. With this new approach, called grid of security, a community of devices ensures that a device is trustworthy and that communications between devices progress in respect of the control of the system policies. To support this approach, we present a new communication model that helps structuring the distribution of security services among the devices. Like this, we can secure both ad-hoc, local-area or enterprise networks in a decentralized manner, preventing the risk of a security breach in the case of a failure.

International audience; Recent advances in communication technology en- able the emergence of a new generation of applications that integrates mobile devices with classical high performance systems as part of a common computing environment. In such environ- ments, keeping the coherence of shared data (distributed objects, for example) represents a real challenge as communications are strongly influenced by the performance and the reliability of mobile devices (laptops, PDAs and cellular telephones) and wireless networks (WiFi, Bluetooth). Indeed, data incoherence may arise due to message losses or node volatility, which blocks the algorithms used to synchronize these data. In this paper, we analyze the main challenges concerning the manipulation of shared distributed objects in a pervasive environment. We demonstrate how a membership service can be enhanced to tolerate temporary disconnections and message losses without blocking, while reducing the number of exchanged message.

International audience; OpenMP has gained wide popularity as an API for parallel programming on shared memory and distributed shared memory platforms. It is also a promising candidate to exploit the emerging multi-core, multi-threaded processors. In addition, there is an increasing trend to port OpenMP to more specific architectures like General Purpose Graphic Processor Units (GPGPUs). However, these ccNUMA (cache coherent Non-Uniform Memory Access) architectures may present several hierarchical memory levels, which represent a serious performance issue for OpenMP applications. In this work, we present the initial results from our effort to quantify and model the impact of memory access heterogeneity on the performance of the applications. Using a simplified performance model, we show how to identify a "performance signature" for a given platform, which allows us to predict the performance of sam- ple applications.

International audience; Due to the increasing diversity and the continuous evolution of existing parallel systems, solving efficiently a target problem by using a single algorithm or writing efficient and portable programs is becoming a challenging task. In this paper, we present a generic framework that integrates performance models with adaptive techniques in order to design efficient parallel algorithms in heterogeneous computing environments. To illustrate our approach, we study the matrix multiplication problem, where we compare different parallel algorithms. Experiments demonstrate that accurate performance predictions obtained from analytical performance models allow us to select the most appropriate algorithm to use depending on the problem and the platform parameters.

Total Order Broadcast protocols are important tools to ensure coherence across distributed systems. Contrarily to classical distributed systems, pervasive systems bring important constraints related to the performance and reliability of the network and the availability of the devices (laptops, PDAs and cellular telephones). We propose in this paper a self-stabilizing group membership service that helps a token-based Total Order Broadcast protocol to progress in a volatile environment. This group membership service is organized in two hierarchical levels so that unstable nodes are kept in the group without interfering with the Total Order Broadcast protocol. As a result, we avoid expensive membership view changes while keeping the coherence among the nodes. ispartof: pages:2202-2206 ispartof: Proceedings of the 23rd Annual ACM Symposium on Applied Computing pages:2202-2206 ispartof: Symposium on Applied Computing location:Fortaleza, Brazil date:16 Mar - 20 Mar 2008 status: published

Collective communication operations are widely used in MPI applications and play an important role in their performance. However, the network heterogeneity inherent to grid environments represent a great challenge to develop efficient high performance computing applications. In this work we propose a generic framework based on communication models and adaptive techniques for dealing with collective communication patterns on grid platforms. Toward this goal, we address the hierarchical organization of the grid, selecting the most efficient communication algorithms at each network level. Our framework is also adaptive to grid load dynamics since it considers transient network characteristics for dividing the nodes into clusters. Our experiments with the broadcast operation on a real-grid setup indicate that an adaptive framework allows significant performance improvements on MPI collective communications.

Paper written in Portuguese; As operações de coordenação em ambientes puramente assíncronos sujeitos a falhas sofrem problemas devido à impossibilidade de distingüir processos falhos de processos muito lentos. Detectores de defeitos representam uma das formas mais eficientes e gerais de circundar tal problema. Entretanto, a diversidade de modelos de detectores sugeridos na bibliografia não foi acompanhada de um estudo comparativo entre as propostas, e até hoje a escolha de um ou outro modelo baseia-se em suposições sem a devida comprovação. O presente trabalho pretende fazer tal comparação, tomando por base um trabalho mais restrito identificado na literatura, mas procurando levantar o máximo possível de características que possam auxiliar a escolha do modelo de detector mais adequado a cada situação.

A transposição de um modelo teórico para uma implementação costuma apresentar diversos problemas inesperados. No caso dos detectores de defeitos, a carência de publicações que demonstrem tais experiências muitas vezes leva a esforços duplicados e atrasos na solução dos problemas. Este artigo apresenta a experiência e as observações realizadas durante o desenvolvimento de um detector de defeitos Heartbeat, ilustrando bem os problemas desta transposição e quais soluções práticas foram tomadas neste experimento.

International audience; The quality of the harvest depends significantly on the quality of the grapes. Therefore, winemakers need to make the right decisions to obtain highquality grapes. One of the first problems is estimating the yield of the crops. It allows winemakers to respect the specific norms of their appellation (yield quota, alcohol levels, etc.). It is also necessary to organise the logistics of the harvest (start date, human resources required, transportations, etc.). Traditionally, the yield estimation is performed by collecting grapes and berries over small, randomised samples, a destructive and laborious task. This work explores how automatic data acquisition combined with artificial intelligence can drive an automated and non-destructive yield estimation, adapted to the characteristics of each vine parcel.

Paper written in Portuguese; Lançada quase simultaneamente à popularização da Internet, a linguagem Java destacou-se como uma linguagem orientada a objetos com importantes características de segurança, integração com os serviços de rede e robustez das aplicações, em ambientes multiplataforma, nas mais distribuídas e heterogêneas redes. Mais que isso, Java implementou conceitos de programação que sempre eram citados como "seria bom que existisse, mas ainda não existe nas linguagens comumente utilizadas". Cabe ressaltar, no entanto, que para a grande maioria das pessoas que já ouviram falar em Java existe uma certa "névoa de mistério", onde praticamente todos sabem que dá pra fazer animações para páginas de WWW, mas não conseguem imaginar outras aplicações ou ferramentas da linguagem. Quando foi proposta a implementação de uma situação de corrida crítica que nem o Produtor-Consumidor, nossa motivação foi a de desvendar os mistérios e capacidades da linguagem Java, aplicando-a da melhor forma possível para chegar ao nosso objetivo. Mais do que isso, devido à característica facilidade com que aplicações Java podem ser integradas às páginas na Internet, a disponibilização da aplicação e do código podem vir a fornecer recursos para pesquisa e desenvolvimento, tanto voltados à área de Sistemas Operacionais, quanto à própria linguagem Java.

International audience; This paper deals with the problem of broadcasting for clus- ter of clusters. The construction of partial minimum spanning trees being NP-complete, several heuristic algorithms have been already formulated. Many of these heuristics (like the heuristic of Kruskal) use the shortest path to connect the components of the tree. They are not relevant in case of forwarding or overlapping communication during a step of the algorithm. In this paper, we study a new heuristic for the minimum broadcasting tree and we evaluate it through simulations with different communication parameters and also through real experimentation over the Grid'5000 testbed.

International audience; The increase in computational capacities has helped in the exploration , production and research process, this has allowed the use of applications that were infeasible years ago. This increase brings us a new Era (known as Post-Moore Era) and a wide range of promising devices, devices such as Single Board Computers (SBC) or Personal Computers (PC) that achieve performance that a decade ago was only found on a Server. This work presents high performance computing devices with low monetary cost and low energy cost that meet the needs for the development of research in Artificial Intelligent (AI) applications, in-situ data analysis and simulations that can be implemented on a large scale, these devices are compared in different tests, presenting advantages such as its performance per watt consumed, smart form, among others.

International audience; Computing systems with a large number of processing units are increasingly common, both in the form of processors employing multiple execution cores (e.g., multi-core CPUs, GPUs, accelerators), or computing clusters with a large number of nodes. These many- core architectures bring up new capabilities, opportunities, as well as challenges. Adapting applications effectively use these architectures has involved a significant amount of effort, not only in code modifications, but also in developing the programming environment. However, several industry trends seem to indicate that large-scale homogeneous platforms, which contain a single type of compute engine with a relatively straightforward memory hierarchy, will soon be a thing of the past. The expansion of heterogeneity in multiple dimensions - compute, memory, storage, systems, software, applications, and usage models – leverages an extreme heterogeneity scenario that will affect both the processor industry but also the software industry, with strong repercussions on programming models, scientific workflows and data management systems. In this talk we examine how high-performance computing has changed over the last 10 years, what are the current projects towards exaflop computing, and look toward the future in terms of trends.

Paper written in Portuguese

International audience; Le Fog Computing étend le paradigme du Cloud Computing à la périphérie du réseau, en s'appuyant sur des services intelligemment distribués pour répondre au mieux aux besoins des applications. Souvent, ces services sont déployés sur des dispositifs "passerelle" caractéri-sés par une puissance de calcul relativement limitée, ce qui peut porter atteinte aux objectifs de qualité de service à l'origine de la démarche fog. Pour mieux comprendre les enjeux, cet article s'intéresse aux performances de l'accès aux données distribuées à partir de dispositifs de proxi-mité tels que les "systèmes sur puce". Des résultats expérimentaux comparant les performances d'accès aux données viennent démontrer l'intérêt de la prise en compte de ces performances lors du déploiement d'une architecture fog.