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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/Simulation%20simtech%20SimTech%20parallel"><owl:Ontology rdf:about=""><rdfs:comment>PUMA publications for /tag/Simulation%20simtech%20SimTech%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><rdf:Description rdf:about="https://puma.ub.uni-stuttgart.de/bibtex/2a102ad88594647037e1fc695a9f77c90/clausbraun"><owl:sameAs rdf:resource="/uri/bibtex/2a102ad88594647037e1fc695a9f77c90/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 IEEE International Conference on Bioinformatics and Biomedicine (BIBM&#039;12)</swrc:booktitle><swrc:pages>1--6</swrc:pages><swrc:title>{Parallel Simulation of Apoptotic Receptor-Clustering on GPGPU Many-Core Architectures}</swrc:title><swrc:year>2012</swrc:year><swrc:keywords>GPGPU SimTech apoptosis modeling myown numerical parallel particle receptor-clustering simulation </swrc:keywords><swrc:abstract>Apoptosis, the programmed cell death, is a physiological process that handles the removal of unwanted or damaged cells in living organisms. The process itself is initiated by signaling through tumor necrosis factor (TNF) receptors and ligands, which form clusters on the cell membrane. The exact function of this process is not yet fully understood and currently subject of basic research. Different mathematical models have been developed to describe and simulate the apoptotic receptor-clustering.
In this interdisciplinary work, a previously introduced model of the apoptotic receptor-clustering has been extended by a new receptor type to allow a more precise description and simulation of the signaling process. Due to the high computational requirements of the model, an ef?cient algorithmic mapping to a modern many-core GPGPU architecture has been developed. Such architectures enable high-performance computing (HPC) simulation tasks on the desktop at low costs. The developed mapping reduces average simulation times from months to days (peak speedup of 256x), allowing the productive use of the model in research.</swrc:abstract><swrc:hasExtraField><swrc:Field swrc:value="http://www.iti.uni-stuttgart.de//fileadmin/rami/files/publications/2012/BIBM_BraunDSSW2012.pdf" swrc:key="file"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="http://dx.doi.org/10.1109/BIBM.2012.6392661" 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="Markus Daub"/></rdf:_2><rdf:_3><swrc:Person swrc:name="Alexander Schöll"/></rdf:_3><rdf:_4><swrc:Person swrc:name="Guido Schneider"/></rdf:_4><rdf:_5><swrc:Person swrc:name="Hans-Joachim Wunderlich"/></rdf:_5></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="https://puma.ub.uni-stuttgart.de/bibtex/2b9d42307aff55f949dce3efdc063ee86/clausbraun"><owl:sameAs rdf:resource="/uri/bibtex/2b9d42307aff55f949dce3efdc063ee86/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 IEEE International Conference on Bioinformatics and Biomedicine (BIBM&#039;14)</swrc:booktitle><swrc:pages>424--431</swrc:pages><swrc:title>{Adaptive Parallel Simulation of a Two-Timescale-Model for Apoptotic Receptor-Clustering on GPUs}</swrc:title><swrc:year>2014</swrc:year><swrc:keywords>Euler-Maruyama GPU SimTech adaptive aggregation approximation computing heterogeneous ligand-receptor-model multi-timescale myown parallel particle simulation </swrc:keywords><swrc:abstract>Computational biology contributes important solutions for major biological challenges. Unfortunately, most applications in computational biology are highly computeintensive and associated with extensive computing times. Biological problems of interest are often not treatable with traditional simulation models on conventional multi-core CPU systems. This interdisciplinary work introduces a new multi-timescale simulation model for apoptotic receptor-clustering and a new parallel evaluation algorithm that exploits the computational performance of heterogeneous CPU-GPU computing systems. For this purpose, the different dynamics involved in receptor-clustering are separated and simulated on two timescales. Additionally, the time step sizes are adaptively refined on each timescale independently.
 This new approach improves the simulation performance significantly and reduces computing times from months to hours for observation times of several seconds.</swrc:abstract><swrc:hasExtraField><swrc:Field swrc:value="http://www.iti.uni-stuttgart.de/fileadmin/rami/files/publications/2014/BIBM_SchoeBDSW2014.pdf" swrc:key="file"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="http://dx.doi.org/10.1109/BIBM.2014.6999195" swrc:key="doi"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Alexander Schöll"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Claus Braun"/></rdf:_2><rdf:_3><swrc:Person swrc:name="Markus Daub"/></rdf:_3><rdf:_4><swrc:Person swrc:name="Guido Schneider"/></rdf:_4><rdf:_5><swrc:Person swrc:name="Hans-Joachim Wunderlich"/></rdf:_5></rdf:Seq></swrc:author></rdf:Description><foaf:Group rdf:about="https://puma.ub.uni-stuttgart.de/tag/Simulation%20simtech%20SimTech%20parallel"><foaf:name>Simulation simtech SimTech parallel</foaf:name><description>Community for tag(s) Simulation simtech SimTech parallel</description></foaf:Group></rdf:RDF>