An efficient version of the RMA-11 model
Abstract RMA-11 is a numerical model widely used for studing the transport of constituents and water quality in rivers and estuaries. When applied to large water systems like the Río de la Plata, RMA-11 demands long execution times to compute a simulation. This paper presents the analysis of the computational efficiency for the RMA-11 applied to a transport model of the Río de la Plata, and introduces a proposal for improving the efficiency by using high performance computing techniques. The improved implementation modifies the linear system resolution methodology implemented in the model. A high performance computing strategy was applied to the FRONTALL routine of the RMA-11, by changing their logical structure and using a sparse storage format. The experimental results obtained when solving representative test cases show a significant improvement on the performance, achieving significant gains in computational speed: the execution time of the implemented version decreased up to one third of the time of the original implementation.
| Main Authors: | , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Centro Latinoamericano de Estudios en Informática
2011
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| Online Access: | http://www.scielo.edu.uy/scielo.php?script=sci_arttext&pid=S0717-50002011000200004 |
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| Summary: | Abstract RMA-11 is a numerical model widely used for studing the transport of constituents and water quality in rivers and estuaries. When applied to large water systems like the Río de la Plata, RMA-11 demands long execution times to compute a simulation. This paper presents the analysis of the computational efficiency for the RMA-11 applied to a transport model of the Río de la Plata, and introduces a proposal for improving the efficiency by using high performance computing techniques. The improved implementation modifies the linear system resolution methodology implemented in the model. A high performance computing strategy was applied to the FRONTALL routine of the RMA-11, by changing their logical structure and using a sparse storage format. The experimental results obtained when solving representative test cases show a significant improvement on the performance, achieving significant gains in computational speed: the execution time of the implemented version decreased up to one third of the time of the original implementation. |
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