Download Achievements in European Research on Grid Systems: CoreGRID by Sergei Gorlatch, Marian Bubak, Thierry Priol PDF

By Sergei Gorlatch, Marian Bubak, Thierry Priol

This quantity contains the edited court cases of the second one CoreGRID Integration Workshop, CGIW'2006, held October 2006 in Krakow, Poland. A "Network of Excellence" funded through the eu Commission’s 6th Framework application, CoreGRID goals to reinforce and enhance medical and technological excellence within the zone of Grid and Peer-to-Peer applied sciences through bringing jointly a severe mass of well-established researchers from forty-one eu study associations. Designed for a certified viewers of practitioners and researchers, the amount is additionally appropriate for advanced-level scholars in desktop technological know-how.

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Personal communication, June 2006. [3] C. An. Personal communication, March 2006. [4] D. Anderson. BOINC: A system for public-resource computing and storage. In 5th IEEE/ACM International Workshop on Grid Computing, Pittsburgh, USA, 2004. [5] D. Antonelli, A. Cordero, and A. Mettler. Securing Distributed Computation with Untrusted Participants. 2004. [6] J. Bohannon. Grassroots supercomputing. Science, 308(6 May):810–813, 2005. [7] C. Christensen, T. Aina, and D. Stainforth. The challenge of volunteer computing with lengthy climate model simulations.

In other words, if we reschedule the task as soon as the error in the checkpoint is detected, W represents the maximum time that we can save, relatively to the compare-at-end approach, with a single error detection. However, in the regular strategy, the computation time can be even worse than T + W , because other errors can delay the task even further. Hence, if we are able to calculate W , we can have a measure of the advantage of detecting errors by comparing intermediate checkpoints. To calculate the expected value of W , we proceed as follows (we omit the probability of not having any error, as there is no gain in that case): m pq E[W ] = i=1 i−1 m−i · T m m q = Tp i=1 i−1 1 − m m i · q i−1 i=1 (1) 19 Validating Desktop Grid Results by Comparing Intermediate Checkpoints Where q = 1 − p.

Checkpointing is a common solution to cope with volatility, and some support exists for application-level checkpointing in desktop grid middleware, such as BOINC and XtremWeb [15]. Result correctness of computations performed on volunteer resources is an important issue, since interpreting incorrect results as correct can be worse than no results at all. A major source of result incorrectness is faulty hardware. In [4], Anderson cites overclocking as a significant cause of faulty computations in projects that resort to the BOINC framework.

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