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   <ow:Publication rdf:about="oai:digibug.ugr.es:10481/59743">
      <dc:title>Dynamic Load Balancing Strategy for Parallel Tumor Growth Simulations</dc:title>
      <dc:creator>Salguero, Alberto G.</dc:creator>
      <dc:creator>Tomeu Hardasmal, Antonio J.</dc:creator>
      <dc:creator>Capel Tuñón, Manuel Isidoro</dc:creator>
      <dc:subject>Cellular Automaton</dc:subject>
      <dc:subject>High-performance computing</dc:subject>
      <dc:subject>Mathematical Oncology</dc:subject>
      <dc:subject>Tumoral Growth Simulation</dc:subject>
      <dc:subject>Parallel programming</dc:subject>
      <dc:description>In this paper, we propose a parallel cellular automaton tumor growth model that includes load balancing of&#xd;
cells distribution among computational threads with the introduction of adjusting parameters. The obtained&#xd;
results show a fair reduction in execution time and improved speedup compared with the sequential tumor&#xd;
growth simulation program currently referenced in tumoral biology. The dynamic data structures of the model&#xd;
can be extended to address additional tumor growth characteristics such as angiogenesis and nutrient intake&#xd;
dependencies</dc:description>
      <dc:date>2020-02-18T08:32:21Z</dc:date>
      <dc:date>2020-02-18T08:32:21Z</dc:date>
      <dc:date>2019</dc:date>
      <dc:type>journal article</dc:type>
      <dc:identifier>Salguero, A. G., Tomeu-Hardasmal, A. J., &amp; Capel, M. I. (2019). Dynamic load balancing strategy for parallel tumor growth simulations. Journal of integrative bioinformatics, 16(1).</dc:identifier>
      <dc:identifier>http://hdl.handle.net/10481/59743</dc:identifier>
      <dc:identifier>10.1515/jib-2018-0066</dc:identifier>
      <dc:language>eng</dc:language>
      <dc:rights>http://creativecommons.org/licenses/by/3.0/es/</dc:rights>
      <dc:rights>open access</dc:rights>
      <dc:rights>Atribución 3.0 España</dc:rights>
      <dc:publisher>Walter de Gruyter GmbH</dc:publisher>
   </ow:Publication>
</rdf:RDF>