Global Computing achieves high throughput computing by harvesting a very large number of unused computing resources connected to the Internet. This parallel computing model targets a parallel architecture defined by a very high number of nodes, poor communication performance and continuously varying resources. The unprecedented scale of the Global Computing architecture paradigm requires to revisit many basic issues related to parallel architecture : programming models, performance models, and class of applications or algorithms suitable to this architecture. Xtreni Web is an experimental Global Computing platform dedicated to provide a tool f o r such studies, This paper presents the design of Xtreni Web. Two essential features of this design are multi-applications and high-performance. Accepting multiple applications allows institutions or enterprises to setup their own Global Computing applications or experiments. High-performance is ensured by scalability, fault tolerance, efJicient scheduling and a large base of volunteer PCs. We also present an implementation of the first global application running on Xtrem Web,

ISBN: 0-7695-152International audienceGlobal Computing platforms, large scale clusters and future TeraGRID systems gather thousands of nodes for computing parallel scientific applications. At this scale, node failures or disconnections are frequent events. This Volatility reduces the MTBF of the whole system in the range of hours or minutes. We present MPICH-V, an automatic Volatility tolerant MPI environment based on uncoordinated checkpoint/roll-back and distributed message logging. MPICH-V architecture relies on Channel Memories, Checkpoint servers and theoretically proven protocols to execute existing or new, SPMD and Master-Worker MPI applications on volatile nodes. To evaluate its capabilities, we run MPICH-V within a framework for which the number of nodes, Channels Memories and Checkpoint Servers can be completely configured as well as the node Volatility. We present a detailed performance evaluation of every component of MPICH-V and its global performance for non-trivial parallel applications. Experimental results demonstrate good scalability and high tolerance to node volatility

Volunteer computing" uses Internet-connected computers, volunteered by their owners, as a source of computing power and storage. This paper studies the potential capacity of volunteer computing. We analyzed measurements of over 330,000 hosts participating in a volunteer computing project. These measurements include processing power, memory, disk space, network throughput, host availability, userspecified limits on resource usage, and host churn. We show that volunteer computing can support applications that are significantly more data-intensive, or have larger memory and storage requirements, than those in current projects.

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Abstract. Desktop grids use the free resources in Intranet and Internet environments for large-scale computation and storage. While desktop grids offer a high return on investment, one critical issue is the validation of results returned by participating hosts. Several mechanisms for result validation have been previously proposed. However, the characterization of errors is poorly understood. To study error rates, we implemented and deployed a desktop grid application across several thousand hosts distributed over the Internet. We then analyzed the results to give quantitative and empirical characterization of errors stemming from input or output (I/O) failures. We find that in practice, error rates are widespread across hosts but occur relatively infrequently. Moreover, we find that error rates tend to not be stationary over time nor correlated between hosts. In light of these characterization results, we evaluated state-ofthe-art error detection mechanisms and describe the trade-offs for using each mechanism.

Abstract:Desktop Grids use the computing, network and storage resources from idle desktop PC's distributed over multiple-LAN's or the Internet to compute a large variety of resource-demanding distributed applications. While these applications need to access, compute, store and circulate large volumes of data, little attention has been paid to data management in such large-scale, dynamic, heterogeneous, volatile and highly distributed Grids. In most cases, data management relies on ad-hoc solutions, and providing general approach is still a challenging issue.To address this problem, we propose the BitDew framework, a programmable environment for automatic and transparent data management on computational Desktop Grids. This paper describes the BitDew programming interface, its architecture, and the performance evaluation of its runtime components. BitDew relies on a specific set of meta-data to drive key data management operations, namely life cycle, distribution, placement, replication and fault-tolerance with a high level of abstraction. The Bitdew runtime environment is a flexible distributed service architecture that integrates modular P2P components such as DHT's for a distributed data catalog and collaborative transport protocols for data distribution. Through several examples, we describe how application programmers and Bitdew users can exploit Bitdew's features. The performance evaluation demonstrates that the high level of abstraction and transparency is obtained with a reasonable overhead, while offering the benefit of scalability, performance and fault tolerance with little programming cost.

Desktop Grids, such as XtremWeb and BOINC, and Service Grids, such as EGEE, are two different approaches for science communities to gather computing power from a large number of computing resources. Nevertheless, little work has been done to combine these two Grid technologies in order to establish a seamless and vast Grid resource pool. In this paper we present the EGEE Service Grid, the BOINC and XtremWeb Desktop Grids. Then, we present the EDGeS solution to bridge the EGEE Service Grid with the BOINC and XtremWeb Desktop Grids