Abstract
An effective approach for improving the efficiency of multi-scale combustion simulations is the use of on-line scientific databases. These databases allow for the approximation of computationally expensive functions by archiving previously computed exact values. A sequential software implementation of these database algorithms has proven to be extremely effective in decreasing the running time of complex reacting flow simulations. To enable the use of this approach on parallel computers, in this paper we introduce three heuristics for coordinating the distributed management of the database. We compare the performance of these heuristics on two limiting case test problems. These experiments demonstrate that a hybrid communication strategy offers the best promise for a large-scale, parallel implementation.
This work was supported by NSF grants CTS-0121573, ACI–9908057, and DGE–9987589 and ACI-0305743.
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Veljkovic, I., Plassmann, P.E. (2006). Parallel Heuristics for an On-Line Scientific Database for Efficient Function Approximation. In: Dongarra, J., Madsen, K., Waśniewski, J. (eds) Applied Parallel Computing. State of the Art in Scientific Computing. PARA 2004. Lecture Notes in Computer Science, vol 3732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558958_77
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DOI: https://doi.org/10.1007/11558958_77
Publisher Name: Springer, Berlin, Heidelberg
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