Frédéric Desprez

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Large scale distributed systems like Grids are difficult to study only from theoretical models and simulators. Most Grids deployed at large scale are production platforms that are inappropriate research tools because of their limited reconfiguration, control and monitoring capabilities. In this paper, we present Grid’5000, a 5000 CPUs nation-wide(More)
Large scale distributed systems like Grid gather several characteristics making them difficult to study only from theoretical models and simulators. Most of Grid deployed at large scale are production platforms making them inappropriate research tools because of their limited reconfiguration, control and monitoring capabilities. In this paper, we present(More)
Among existing grid middleware approaches, one simple, powerful, and flexible approach consists of using servers available in different administrative domains through the classical client-server or Remote Procedure Call (RPC) paradigm. Network Enabled Servers implement this model also called GridRPC. Clients submit computation requests to a scheduler whose(More)
This article is devoted to the run-time redistribution of arrays that are distributed in a blockcyclic fashion over a multidimensional processor grid. While previous studies have concentrated on e ciently generating the communication messages to be exchanged by the processors involved in the redistribution, we focus on the scheduling of those messages: how(More)
The Cloud phenomenon brings along the cost-saving benefit of dynamic scaling. As a result, the question of efficient resource scaling arises. Prediction is necessary as the virtual resources that Cloud computing uses have a setup time that is not negligible. We propose an approach to the problem of workload prediction based on identifying similar past(More)
The GridRPC model (Nakada et al., 2003) is an emerging standard promoted by the Global Grid Forum (GGF) that defines how to perform remote client-server computation on a distributed architecture. In this model data are sent back to the client at the end of every computation. This implies unnecessary communications when computed data are needed by another(More)
Mixed-parallelism, the combination of dataand taskparallelism, is a powerful way of increasing the scalability of entire classes of parallel applications on platforms comprising multiple compute clusters. While multi-cluster platforms are predominantly heterogeneous, previous work on mixed-parallel application scheduling targets only homogeneous platforms.(More)
The GridRPC model [17] is an emerging standard promoted by the Global Grid Forum (GGF) that defines how to perform remote client-server computations on a distributed architecture. In this model data are sent back to the client at the end of every computation. This implies unnecessary communications when computed data are needed by an other server in further(More)
Many scienti c applications are described through work ow structures. Due to the increasing level of parallelism o ered by modern computing infrastructures, work ow applications now have to be composed not only of sequential programs, but also of parallel ones. Cloud platforms bring on-demand resource provisioning and pay-as-you-go payment charging. Then(More)
The cloud phenomenon is quickly growing towards becoming the de facto standard of Internet computing, storage and hosting both in industry and academia. The large scalability possibilities offered by cloud platforms can be harnessed not only for services and applications hosting but also as a raw on-demand computing resource. This paper proposes the use of(More)