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Semi-automatic parallelization of direct and inverse problems for geothermal simulation

Published: 08 March 2009 Publication History

Abstract

We describe a strategy for parallelizing a geothermal simulation package using the shared-memory programming model OpenMP. During the code development OpenMP is employed for the direct problem in such a way that, in a subsequent step, the OpenMP-parallelized code can be transformed via automatic differentiation into an OpenMP-parallelized code capable of computing derivatives for the inverse problem. Performance results on a Sun Fire X4600 using up to 16 threads are reported demonstrating that, for the derivative computation, an approach using nested parallelism is more scalable than a single level of parallelism.

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cover image ACM Conferences
SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing
March 2009
2347 pages
ISBN:9781605581668
DOI:10.1145/1529282
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 08 March 2009

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Author Tags

  1. ADIFOR
  2. OpenMP
  3. automatic differentiation
  4. automatic parallelization
  5. forward mode
  6. nested parallelism
  7. shared-memory programming

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SAC09: The 2009 ACM Symposium on Applied Computing
March 8, 2009 - March 12, 2008
Hawaii, Honolulu

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