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<rdf:RDF xmlns:community="http://www.bibsonomy.org/ontologies/2008/05/community#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:admin="http://webns.net/mvcb/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:syn="http://purl.org/rss/1.0/modules/syndication/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns:cc="http://web.resource.org/cc/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" xmlns:swrc="http://swrc.ontoware.org/ontology#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xml:base="https://puma.ub.uni-stuttgart.de/tag/gpu%20SimTech%20computer%20parallel"><owl:Ontology rdf:about=""><rdfs:comment>PUMA publications for /tag/gpu%20SimTech%20computer%20parallel</rdfs:comment><owl:imports rdf:resource="http://swrc.ontoware.org/ontology/portal"/></owl:Ontology><rdf:Description rdf:about="https://puma.ub.uni-stuttgart.de/bibtex/2126f35b3dc5e36c0d63a461eb07e23c3/clausbraun"><owl:sameAs rdf:resource="/uri/bibtex/2126f35b3dc5e36c0d63a461eb07e23c3/clausbraun"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#InProceedings"/><swrc:date>Mon Mar 19 16:15:07 CET 2018</swrc:date><swrc:booktitle>Proceedings of the 30th IEEE International Conference on Computer Design (ICCD&#039;12)</swrc:booktitle><swrc:pages>207--212</swrc:pages><swrc:publisher><swrc:Organization swrc:name="IEEE Computer Society"/></swrc:publisher><swrc:title>{Acceleration of Monte-Carlo Molecular Simulations on Hybrid Computing Architectures}</swrc:title><swrc:year>2012</swrc:year><swrc:keywords>GPGPU GPU Markov-Chain Monte-Carlo SimTech architectures computer heterogeneous hybrid molecular myown parallel simulation thermodynamics </swrc:keywords><swrc:abstract>Markov-Chain Monte-Carlo (MCMC) methods are an important class of simulation techniques, which execute a sequence of simulation steps, where each new step depends on the previous ones. Due to this fundamental dependency, MCMC methods are inherently hard to parallelize on any architecture. The upcoming generations of hybrid CPU/GPGPU architectures with their multi-core CPUs and tightly coupled many-core GPGPUs provide new acceleration opportunities especially for MCMC methods, if the new degrees of freedom are exploited correctly. 
In this paper, the outcomes of an interdisciplinary collaboration are presented, which focused on the parallel mapping of a MCMC molecular simulation from thermodynamics to hybrid CPU/GPGPU computing systems. While the mapping is designed for upcoming hybrid architectures, the implementation of this approach on an NVIDIA Tesla system already leads to a substantial speedup of more than 87x despite the additional communication overheads.</swrc:abstract><swrc:hasExtraField><swrc:Field swrc:value="http://www.iti.uni-stuttgart.de/fileadmin/rami/files/publications/2012/ICCD_BraunHWCG2012.pdf" swrc:key="file"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="http://dx.doi.org/10.1109/ICCD.2012.6378642" swrc:key="doi"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Claus Braun"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Stefan Holst"/></rdf:_2><rdf:_3><swrc:Person swrc:name="Hans-Joachim Wunderlich"/></rdf:_3><rdf:_4><swrc:Person swrc:name="Juan Manuel Castillo"/></rdf:_4><rdf:_5><swrc:Person swrc:name="Joachim Gross"/></rdf:_5></rdf:Seq></swrc:author></rdf:Description><foaf:Group rdf:about="https://puma.ub.uni-stuttgart.de/tag/gpu%20SimTech%20computer%20parallel"><foaf:name>gpu SimTech computer parallel</foaf:name><description>Community for tag(s) gpu SimTech computer parallel</description></foaf:Group></rdf:RDF>