Dataset Open Access
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <identifier identifierType="DOI">10.5281/zenodo.4081080</identifier> <creators> <creator> <creatorName>Brian J. N. Wylie</creatorName> <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-2770-2443</nameIdentifier> <affiliation>Jülich Supercomputing Centre</affiliation> </creator> </creators> <titles> <title>Scalasca summary analysis of HemeLB_GPU application execution with 129 MPI processes on JUWELS/V100</title> </titles> <publisher>Zenodo</publisher> <publicationYear>2020</publicationYear> <subjects> <subject>Scalasca Score-P CUBE HemeLB JUWELS MPI+GPU</subject> </subjects> <dates> <date dateType="Issued">2020-10-12</date> </dates> <resourceType resourceTypeGeneral="Dataset"/> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4081080</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="DOI" relationType="References" resourceTypeGeneral="Text">10.5281/zenodo.3885304</relatedIdentifier> <relatedIdentifier relatedIdentifierType="DOI" relationType="References" resourceTypeGeneral="Text">10.5281/zenodo.3356706</relatedIdentifier> <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4081079</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"><p>The CompBioMed HPC CoE flagship application HemeLB (prototype GPU version) was run with a (patched) arteries geometry dataset on JSC&#39;s JUWELS supercomputer, and its execution performance with 129 MPI processes on 32 dual 20-core CPU + quad V100 GPU compute nodes measured by Score-P and analysed by Scalasca (and Vampir)</p></description> </descriptions> <fundingReferences> <fundingReference> <funderName>European Commission</funderName> <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier> <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/675451/">675451</awardNumber> <awardTitle>A Centre of Excellence in Computational Biomedicine</awardTitle> </fundingReference> <fundingReference> <funderName>European Commission</funderName> <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier> <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/824080/">824080</awardNumber> <awardTitle>Performance Optimisation and Productivity 2</awardTitle> </fundingReference> </fundingReferences> </resource>
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