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Section: Partnerships and Cooperations
National Initiatives
"Action d'envergure"
Leading action "Completing challenging experiments on Grid'5000 (Methodology)"
Experimental platforms like Grid'5000 or PlanetLab provide an invaluable help to the scientific community, by making it possible to run very large-scale experiments in con- trolled environment. However, while performing relatively simple experiments is generally easy, it has been shown that the complexity of completing more challenging experiments (involving a large number of nodes, changes to the environment to introduce heterogeneity or faults, or instrumentation of the platform to extract data during the experiment) is often underestimated.
This working group explores different complementary approaches, that are the basic building blocks for building the next level of experimentation on large scale experimental platforms. This encompasses several aspects.
ARC Inria
Partners: EPI Dionysos, EPI Maestro, EPI MESCAL, EPI Comore, GET/Telecom Bretagne, FTW, Vienna (Forschungszentrum Telekommunikation Wien), Columbia University, USA, Pennsylvania State University, USA, Alcatel-Lucent Bell Labs France, Orange Labs.
The goal of this project is to study the interest of network neutrality, a topic that has recently gained a lot of attention. The project aims at elaborating mathematical models that will be analyzed to investigate its impact on users, on social welfare and on providers' investment incentives, among others, and eventually propose how (and if) network neutrality should be implemented. It brings together experts from different scientific fields, telecommunications, applied mathematics, economics, mixing academy and industry, to discuss those issues. It is a first step towards the elaboration of a European project.
ADT Inria (2)
Partners: Inria Grand Est. Two young engineers have been allotted by the Inria to the SimGrid project to help with the software maintenance and with the transfer of research ideas and prototypes from the ANR USS SimGrid to public stable versions.
Partners: Inria FUTURS, Inria Sophia, IRISA, LORIA, IRIT, LABRI, LIP, LIFL.
After the success of the Grid'5000 project of the ACI Grid initiative led by the French ministry of research, Inria is launching the ALADDIN project to further develop the Grid'5000 infrastructure and foster scientific research using the infrastructure.
ALADDIN built on Grid'5000's experience to provide an infrastructure enabling computer scientists to conduct experiments on large scale computing and produced scientific results that can be reproduced by others.
MESCAL members are particularly involved in efficient large scale system utilization, providing confidence to the user about the infrastructure and modeling of large scale systems and validation of their simulators.
NANO 2012
Rapid advances in multi-core technologies have been incorporated in general-purpose processors from Intel, IBM, Sun, and AMD, and special-purpose graphics processors from NVIDIA and ATI. This technology will soon be introduced to the next generation of processors in embedded systems. The increase in the number of cores per processor will introduce critical challenges for the access of data stored in memory. The synchronization of memory accesses is often done using the use of locks for shared variables. As the number of threads increases, the cost of synchronization also increases due to increased access to these shared variables. Transactional memory is currently an approach being actively investigated. The goal of this project is to improve the programability and performance of parallel systems using the approach of transactional memory in the context of embedded systems.
ANR Jeunes Chercheurs et Jeunes Chercheuses (2)
The race towards the design and development of scalable distributed systems offers new opportunities to applications, in particular as far as scientific computing, databases, and file sharing are concerned. Recently many advances have been done in the area of large-scale file-sharing systems, building upon the peer-to-peer paradigm that somehow seamlessly responds to the dynamicity and resilience issues. However, achieving a fair resource sharing amongst a large number of users in a distributed way is clearly still an open and active research field. For all previous issues there is a clear gap between:
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widely deployed systems as peer-to-peer file-sharing systems (KaZaA, Gnutella, EDonkey) that are generally not very efficient and do not propose generic solutions that can be extended to other kind of usage;
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academic work with generally smart solutions (probabilistic routing in random graphs, set of node-disjoint trees, Lagrangian optimization) that sometimes lack a real application.
Up to now, the main achievements based on the peer-to-peer paradigm mainly concern file- sharing issues. We believe that a large class of scientific computations could also take advantage of this kind of organization. Thus our goal is to design a peer-to-peer computing infrastructure with a particular emphasis on the fairness issues. In particular, the objectives of the ANR DOCCA(Design and Optimization of Collaborative Computing Architectures) project are the following:
First, we want to combine theoretical tools and metrics from the parallel computing community and from the network community, and to explore algorithmic and analytical solutions to the specific resource management problems of such systems.
We also want to design a P2P architecture based on the algorithms designed in the second step, and to create a novel P2P collaborative computing system.
The overall objective of this project is to design and develop a cloud computing platform that enables the execution of complex services and applications over unreliable volunteered resources over the Internet. In terms of reliability, these resources are often unavailable 40% of the time, and exhibit frequent churn (several times a day). In terms of "real, complex services and applications", we refer to large-scale service deployments, such as Amazon's EC2, the TeraGrid, and the EGEE, and also applications with complex dependencies among tasks. These commercial and scientific services and applications need guaranteed availability levels of 99.999% for computational, network, and storage resources in order to have efficient and timely execution.
ANR COSI
Partners: Bull SAS, CAPS entreprise, CEA CESTA, CEA INAC, Inria RUNTIME, UVSQ PriSM
Processor architectures with many-core processors and special-purpose processors such as GPUS and the CELL processor have recently emerged. These new and heterogeneous architectures require new application programming methods and new programming models. The goal of the ProHMPT project is to address this challenge by focusing on the immense computing needs and requirements of real simulations for nanotechnologies. In order for nanosimulations to fully leverage heterogeneous computing architectures, project members will novel technologies at the compiler, runtime, and scientific kernely levels with proper abstractions and wide portability. This project brings experts from industry, in particular HPC hardware expertise from Bull and nanosimulation expertise from CEA.
ANR ARPEGE
Partners: RealTimeAtWork, Thales, ONERA, ENS Cachan
The goal of this project to achieve performance guarantees for communicating embedded systems. Members will develop mathematical methods that give accurate bounds on maximum network delays in both space and aviation systems. The mathematical methods will be based on Network Calculus theory, which is type of queuing theory that deals with worst-case performance evaluation. The expected results will be novel models and software tools validated in mission-critical real-time embedded networks of the aerospace industry.
ANR SEGI (2)
Partners: Inria Nancy, Inria Sophia, Inria Bordeaux, University of Reims, IN2P3, University of Hawaii at Manoa
The goal of the USS-SimGrid project is to enable scalable and accurate simulations by means of the SimGrid simulation toolkit. This toolkit is widely used for simulation of Grid systems. We aim to extend the functionality of the toolkit to enable the simulation of heterogeneous systems with more than tens of thousands of nodes.
There are three main thrusts in this project. First, we improve the models used in SimGrid, increasing their scalability and easing their instantiation. Second, we develop tools that ease the analysis of detailed and large simulation results, and aid the management of simulation deployments. Third, we improve the scalability of simulations using parallelization and optimization methods. A mid-term report summarizing our findings has been published in [59] .
Partners: Inria GRAAL, Inria GRAND-LARGE, CERFACS, CNRS, Inria PARIS, LORIA
Petascale systems consisting of thousands to millions of resources have emerged. At the same, existing infrastructure are not capable of fully harnessing the computational power of such systems. The SPADES project will address several challenges in such large systems. First, the members are investigating methods for service discovery in volatile and dynamic platforms. Second, the members creating novel models of reliability in PetaScale systems. Third, the members will develop stochastic scheduling methods that leverage these models. This will be done with emphasis on applications with task dependencies structured as graph.