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International Parallel and Distributed Processing Symposium (IPDPS'03)
An Approach to Optimizing Adaptive Parabolic PDE Solvers for the Grid
Nice, France
April 22-April 26
ISBN: 0-7695-1926-1
Vikram Adve, University of Illinois
James Browne, University of Texas at Austin
Brian Ensink, University of Illinois
John Rice, Purdue University
Patricia Teller, University of Texas at El Paso,
Mary Vernon, University of Wisconsin - Madison
Stephen Wright, University of Wisconsin - Madison
The Method of Lines is a widely used algorithm for solving parabolic partial differential equations that could benefit greatly from implementation on Grid computing environments. This work outlines the issues involved in executing Method-of-Lines codes on a Grid and in developing model-driven adaptive control strategies for these codes. We have developed a parameterizable benchmark called MOL that captures a wide range of realistic Method-of-Lines codes. We are using this benchmark to develop performance models that can be used to achieve specific optimality criteria under the available (and dynamically varying) resources of a Grid environment, and under user-specified goals for solution error and computational rate-of-progress. We are developing a componentization strategy that can enable effective adaptive control of MOL, as well as language and compiler support that can simplify the development of adaptive distributed applications. If successful, this work should yield a much better understanding than we have at present of how an important class of parallel numerical applications can be executed effectively in a dynamic Grid environment.
Citation:
Vikram Adve, James Browne, Brian Ensink, John Rice, Patricia Teller, Mary Vernon, Stephen Wright, "An Approach to Optimizing Adaptive Parabolic PDE Solvers for the Grid," ipdps, pp.210a, International Parallel and Distributed Processing Symposium (IPDPS'03), 2003
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