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                          <header>
                              <identifier>oai:research.chalmers.se:201332</identifier>
                              <datestamp>2019-02-14T08:14:29Z</datestamp>
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                          <metadata>
                              <oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
                                  <dc:title>Performance of distributed multiscale simulations</dc:title>
                                  <dc:identifier>https://research.chalmers.se/en/publication/201332</dc:identifier>
                                  <dc:date>2014</dc:date>
                                              <dc:creator>Borgdorff, J.</dc:creator>
                                              <dc:creator>Ben Belgacem, M.</dc:creator>
                                              <dc:creator>Bona-Casas, C.</dc:creator>
                                              <dc:creator>Fazendeiro, Luis</dc:creator>
                                              <dc:creator>Groen, D.</dc:creator>
                                              <dc:creator>Hoenen, O.</dc:creator>
                                              <dc:creator>Mizeranschi, A.</dc:creator>
                                              <dc:creator>Suter, J. L.</dc:creator>
                                              <dc:creator>Coster, D.</dc:creator>
                                              <dc:creator>Coveney, P. V.</dc:creator>
                                              <dc:creator>Dubitzky, W.</dc:creator>
                                              <dc:creator>Hoekstra, A. G.</dc:creator>
                                              <dc:creator>Strand, Pär</dc:creator>
                                              <dc:creator>Chopard, B.</dc:creator>
                                                  <dc:subject>Astronomy, Astrophysics and Cosmology</dc:subject>
                                          <dc:description>Multiscale simulations model phenomena across natural scales using monolithic or component-based code, running on local or distributed resources. In this work, we investigate the performance of distributed multiscale computing of component-based models, guided by six multiscale applications with different characteristics and from several disciplines. Three modes of distributed multiscale computing are identified: supplementing local dependencies with large-scale resources, load distribution over multiple resources, and load balancing of small- and large-scale resources. We find that the first mode has the apparent benefit of increasing simulation speed, and the second mode can increase simulation speed if local resources are limited. Depending on resource reservation and model coupling topology, the third mode may result in a reduction of resource consumption.</dc:description>
                                                                  <dc:relation>info:eu-repo/grantAgreement/EC/FP7/261507//Multiscale Applications on European e-Infrastructures (MAPPER)/</dc:relation>
                                                  <dc:relation>info:eu-repo/semantics/altIdentifier/doi/10.1098/rsta.2013.0407</dc:relation>
                                          <dc:type>info:eu-repo/semantics/article</dc:type>
                                          <dc:source>Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences (1364-503X) vol.372(2014)</dc:source>
                                                      <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:language>eng</dc:language>
                                  <dc:audience>Researchers</dc:audience>
                                  <dc:format>application/pdf</dc:format>
                              </oai_dc:dc>
                          </metadata>
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