June 4, 2014 Working paper Open Access

Thomas Röblitz

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  <identifier identifierType="DOI">10.5281/zenodo.823031</identifier>
  <creators>
    <creator>
      <creatorName>Thomas Röblitz</creatorName>
      <affiliation>Department for Research Computing, University Center for Information Technology (USIT), University of Oslo, P.O. Box 1059, Blindern, 0316 Oslo, Norway</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Scaling of Biological Data Work ows to Large HPC Systems - A Case Study in Marine Genomics -</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2014</publicationYear>
  <subjects>
    <subject>workflows, magnitude scaling</subject>
  </subjects>
  <contributors>
    <contributor contributorType="Other">
      <contributorName>Ole W. Saastad</contributorName>
      <affiliation>Department for Research Computing, University Center for Information Technology (USIT), University of Oslo, P.O. Box 1059, Blindern, 0316 Oslo, Norway</affiliation>
    </contributor>
    <contributor contributorType="Other">
      <contributorName>Hans A. Eide</contributorName>
      <affiliation>Department for Research Computing, University Center for Information Technology (USIT), University of Oslo, P.O. Box 1059, Blindern, 0316 Oslo, Norway</affiliation>
    </contributor>
    <contributor contributorType="Other">
      <contributorName>Katerina Michalickova</contributorName>
      <affiliation>Department for Research Computing, University Center for Information Technology (USIT), University of Oslo, P.O. Box 1059, Blindern, 0316 Oslo, Norway</affiliation>
    </contributor>
    <contributor contributorType="Other">
      <contributorName>Alexander Johan Nederbragt</contributorName>
      <affiliation>Center for Ecological and Evolutionary Synthesis, Department of Biosciences (CEES), University of Oslo, P.O. Box 1066, Blindern, 0316 Oslo, Norway</affiliation>
    </contributor>
    <contributor contributorType="Other">
      <contributorName>Bastiaan Star</contributorName>
      <affiliation>Center for Ecological and Evolutionary Synthesis, Department of Biosciences (CEES), University of Oslo, P.O. Box 1066, Blindern, 0316 Oslo, Norway</affiliation>
    </contributor>
  </contributors>
  <dates>
    <date dateType="Issued">2014-06-04</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Working paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/823031</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.823030</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/prace</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Sequencing projects, like the Aqua Genome project, generate vast amounts of data which is processed through dif-&lt;br&gt;
ferent work ows composed of several steps linked together. Currently, such workflows are often run manually on&lt;br&gt;
large servers. With the increasing amount of raw data that approach is no longer feasible. The successful imple-&lt;br&gt;
mentation of the project's goals requires 2-3 orders of magnitude scaling of computing, while achieving high reli-&lt;br&gt;
ability on and supporting ease-of-use of super computing resources at the same time. We describe two example&lt;br&gt;
use cases, the implementation challenges and constraints, the actual application enabling and report our ndings.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/100011102</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/FP7/312763/">312763</awardNumber>
      <awardTitle>PRACE - Third Implementation Phase Project</awardTitle>
    </fundingReference>
  </fundingReferences>
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