Parallelizing a very high resolution climate model using clusters of workstations with PVM and performance and load balance analyses Wang, Hao Prabhu, Gurpur Takle, Eugene Takle, Eugene
dc.contributor.department Aerospace Engineering
dc.contributor.department Ames National Laboratory
dc.contributor.department Computer Science
dc.contributor.department Agronomy
dc.contributor.department Geological and Atmospheric Sciences 2018-02-18T17:56:50.000 2020-06-30T04:03:01Z 2020-06-30T04:03:01Z Thu Jan 01 00:00:00 UTC 1998 2017-07-26 1998
dc.description.abstract <p>Environment and climate change problems are very complicated, and their research and operational prediction heavily depend on powerful computer techniques. Even with today most powerful supercomputer, the climate and environmental models are still limited to very coarse resolution. In this paper, we report our recent effort in parallelizing our very-high-resolution numerical model systems. First, the mathematical equations, algorithms, and numerical schemes are designed and analyzed; then domain decomposition, data decomposition, and functional decomposition schemes are tested in our implementations on clusters of HP workstations and/or DEC Alpha stations with PVM; finally, the performance and load balance are analyzed. Shelterbelts cause significantly inhomogeneous computation distribution on the domain, therefore, common and easiest domain decomposition does not work well on our problem. Special care must be taken to treat computations around shelterbelts. With carefull design of algorithms, we found that cheap and still powerful workstations or PCs make it possible to run these models in clusters of workstations or PCs.</p>
dc.description.comments <p>This proceeding was published as Wang, H., G. Prabhu, and E. S. Takle, 1998: "Parallelizing a very high resolution climate model using clusters of workstations with PVM and performance and load balance analyses." <em>Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications</em>, CSREA Press. pp. 1762-1765. Posted with permission.</p>
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dc.identifier archive/
dc.identifier.articleid 1001
dc.identifier.contextkey 10481671
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath ge_at_conf/2
dc.language.iso en
dc.source.bitstream archive/|||Fri Jan 14 22:09:45 UTC 2022
dc.source.bitstream archive/|||Fri Jan 14 22:09:47 UTC 2022
dc.subject.disciplines Climate
dc.subject.disciplines Databases and Information Systems
dc.subject.disciplines Environmental Monitoring
dc.subject.disciplines Theory and Algorithms
dc.subject.keywords cluster computing
dc.subject.keywords climate model
dc.subject.keywords scientific computing
dc.subject.keywords parallel and distributed algorithm
dc.subject.keywords load balance
dc.subject.keywords numerical analyses
dc.title Parallelizing a very high resolution climate model using clusters of workstations with PVM and performance and load balance analyses
dc.type article
dc.type.genre conference
dspace.entity.type Publication
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