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Parallel and Distributed Processing Symposium, International (2008)
Miami, FL, USA
Apr. 14, 2008 to Apr. 18, 2008
ISBN: 978-1-4244-1693-6
pp: 1-12
Travis Desell , Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY, U.S.A.
Boleslaw Szymanski , Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY, U.S.A.
Carlos Varela , Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY, U.S.A.
ABSTRACT
Use of large-scale heterogeneous computing environments such as computational grids and the Internet has become of high interest to scientific researchers. This is because the increasing complexity of their scientific models and data sets is drastically outpacing the increases in processor speed while the cost of supercomputing environments remains relatively high. However, the heterogeneity and unreliability of these environments, especially the Internet, make scalable and fault tolerant search methods indispensable to effective scientific model verification. The paper introduces two versions of asynchronous master-worker genetic search and evaluates their convergence and performance rates in comparison to traditional synchronous genetic search on both a IBM BlueGene supercomputer and using the MilkyWay@HOME BOINC Internet computing project <sup>1</sup>. The asynchronous searches not only perform faster on heterogeneous grid environments as compared to synchronous search, but also achieve better convergence rates for the astronomy model used as the driving application, providing a strong argument for their use on grid computing environments and by the MilkyWay@Home BOINC internet computing project.
INDEX TERMS
CITATION
Travis Desell, Boleslaw Szymanski, Carlos Varela, "Asynchronous genetic search for scientific modeling on large-scale heterogeneous environments", Parallel and Distributed Processing Symposium, International, vol. 00, no. , pp. 1-12, 2008, doi:10.1109/IPDPS.2008.4536169
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