<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-14T03:00:43Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:2117/118762" metadataPrefix="qdc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:2117/118762</identifier><datestamp>2025-07-22T21:32:13Z</datestamp><setSpec>com_2072_1033</setSpec><setSpec>col_2072_452951</setSpec></header><metadata><qdc:qualifieddc xmlns:qdc="http://dspace.org/qualifieddc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://purl.org/dc/elements/1.1/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dc.xsd http://purl.org/dc/terms/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dcterms.xsd http://dspace.org/qualifieddc/ http://www.ukoln.ac.uk/metadata/dcmi/xmlschema/qualifieddc.xsd">
   <dc:title>Inferring program structure from execution traces</dc:title>
   <dc:creator>Martínez Vera, Juan Francisco</dc:creator>
   <dc:subject>Àrees temàtiques de la UPC::Informàtica</dc:subject>
   <dc:subject>Pattern recognition systems</dc:subject>
   <dc:subject>Computer simulation</dc:subject>
   <dc:subject>Cluster analysis</dc:subject>
   <dc:subject>computació d'alt rendiment</dc:subject>
   <dc:subject>clustering</dc:subject>
   <dc:subject>escalabilitat</dc:subject>
   <dc:subject>minat de patrons seqüencials</dc:subject>
   <dc:subject>eïnes per l'analisi del rendiment</dc:subject>
   <dc:subject>MPI</dc:subject>
   <dc:subject>reconeixement de patrons</dc:subject>
   <dc:subject>aplicacions HPC</dc:subject>
   <dc:subject>high perfomance computing</dc:subject>
   <dc:subject>HPC applications</dc:subject>
   <dc:subject>sequential pattern mining</dc:subject>
   <dc:subject>scalability</dc:subject>
   <dc:subject>application structure detection</dc:subject>
   <dc:subject>performance analysis tools</dc:subject>
   <dc:subject>detecció d'estructura d'aplicacions</dc:subject>
   <dc:subject>Reconeixement de formes (Informàtica)</dc:subject>
   <dc:subject>Simulació per ordinador</dc:subject>
   <dc:subject>Anàlisi de conglomerats</dc:subject>
   <dcterms:abstract>Application structure detection problem have been typical solved by means of sequential pattern mining techniques but they present to be difficultly scalable. In this thesis we propose a new approach for HPC apps facing this problem as a classification problem such that scalability can be improved.</dcterms:abstract>
   <dcterms:issued>2018-04-16</dcterms:issued>
   <dc:type>Master thesis</dc:type>
   <dc:rights>Open Access</dc:rights>
   <dc:publisher>Universitat Politècnica de Catalunya</dc:publisher>
</qdc:qualifieddc></metadata></record></GetRecord></OAI-PMH>