Software Open Access
<?xml version='1.0' encoding='utf-8'?> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:adms="http://www.w3.org/ns/adms#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dct="http://purl.org/dc/terms/" xmlns:dctype="http://purl.org/dc/dcmitype/" xmlns:dcat="http://www.w3.org/ns/dcat#" xmlns:duv="http://www.w3.org/ns/duv#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:frapo="http://purl.org/cerif/frapo/" xmlns:geo="http://www.w3.org/2003/01/geo/wgs84_pos#" xmlns:gsp="http://www.opengis.net/ont/geosparql#" xmlns:locn="http://www.w3.org/ns/locn#" xmlns:org="http://www.w3.org/ns/org#" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:prov="http://www.w3.org/ns/prov#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:schema="http://schema.org/" xmlns:skos="http://www.w3.org/2004/02/skos/core#" xmlns:vcard="http://www.w3.org/2006/vcard/ns#" xmlns:wdrs="http://www.w3.org/2007/05/powder-s#"> <rdf:Description rdf:about="https://doi.org/10.5281/zenodo.1305227"> <rdf:type rdf:resource="http://www.w3.org/ns/dcat#Dataset"/> <dct:type rdf:resource="http://purl.org/dc/dcmitype/Software"/> <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://doi.org/10.5281/zenodo.1305227</dct:identifier> <foaf:page rdf:resource="https://doi.org/10.5281/zenodo.1305227"/> <dct:creator> <rdf:Description rdf:about="http://orcid.org/0000-0001-7904-5639"> <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/> <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">0000-0001-7904-5639</dct:identifier> <foaf:name>Airidas Korolkovas</foaf:name> <org:memberOf> <foaf:Organization> <foaf:name>Uppsala University</foaf:name> </foaf:Organization> </org:memberOf> </rdf:Description> </dct:creator> <dct:title>Pushing the frontiers of polymer simulation with texture memory</dct:title> <dct:publisher> <foaf:Agent> <foaf:name>Zenodo</foaf:name> </foaf:Agent> </dct:publisher> <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2018</dct:issued> <dcat:keyword>GPU, CUDA, textures, polymers, entanglement, reptation</dcat:keyword> <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2018-07-04</dct:issued> <dct:language rdf:resource="http://publications.europa.eu/resource/authority/language/ENG"/> <owl:sameAs rdf:resource="https://zenodo.org/record/1305227"/> <adms:identifier> <adms:Identifier> <skos:notation rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://zenodo.org/record/1305227</skos:notation> <adms:schemeAgency>url</adms:schemeAgency> </adms:Identifier> </adms:identifier> <dct:relation rdf:resource="https://arxiv.org/abs/1805.08508"/> <dct:relation rdf:resource="https://doi.org/10.1002/adts.201800078"/> <dct:isVersionOf rdf:resource="https://doi.org/10.5281/zenodo.1305226"/> <dct:description><p>Pushing the frontiers of polymer simulation with texture memory<br> ---------------------------------------------------------------</p> <p><br> Welcome to the Source Code for simulating entangled star polymers.<br> This custom software was used to generate data for the article &ldquo;Five dimensional entanglement in star polymer dynamics&quot;<br> published in Advanced Theory and Simulations (Wiley)<br> A preprint is available here: https://arxiv.org/abs/1805.08508</p> <p>The demo provided here simulates Brownian dynamics of NS=104 stars with 3 arms, of length N=356 beads per arm.<br> It requires a CUDA-enabled GPU card, which is managed from a Matlab environment using the launchstars.m script.<br> The .cu source files are included and have been pre-compiled for several star sizes using this command:<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; mexcuda mystar356.cu</p> <p>Now simply run:<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; launchstars.m</p> <p>The default settings create the initial polymer configuration in Matlab, which is then transferred to GPU and processed by CUDA for 1000 steps.<br> The resulting configuration is returned to Matlab, and selected data is stored for later analysis.<br> This cycle is repeated 200 times, and the real-space configuration is optionally plotted in 3D (see a snapshot in the Figures folder).<br> Once the demo is complete, you may verify the speed of the computation using this command (it runs an extra numIterations=1000 steps):</p> <p>&nbsp;&nbsp; &nbsp;tic; [R, randvector, ~] = fh(single(gpuArray(R)), randvector, b, vstrong, rstrong, cosbeta, numIterations, timeStep); toc;<br> &nbsp;&nbsp; &nbsp;Elapsed time is 0.398752 seconds.</p> <p>The above figure is for a box of 104*3*356=111072 beads, 1000 iterations, using a Titan XP card donated by the NVIDIA Corporation.<br> The whole demo lasts about 1 minute 30 seconds.<br> The branch point trajectory may be analysed by running the script autodiff.m provided in the Data Analysis Tools folder.<br> A typical result is shown in the MSD.pdf figure. Sub-reptative behaviour (negative slope) is apparent within one minute of simulation.</p> <p><br> Author:<br> Airidas Korolkovas, PhD<br> Institut Laue-Langevin<br> Uppsala University<br> korolkovas@ill.fr<br> airidas.korolkovas89@gmail.com</p> <p>July 04, 2018</p></dct:description> <dct:accessRights rdf:resource="http://publications.europa.eu/resource/authority/access-right/PUBLIC"/> <dct:accessRights> <dct:RightsStatement rdf:about="info:eu-repo/semantics/openAccess"> <rdfs:label>Open Access</rdfs:label> </dct:RightsStatement> </dct:accessRights> <dcat:distribution> <dcat:Distribution> <dct:license rdf:resource="https://creativecommons.org/licenses/by/4.0/legalcode"/> <dcat:accessURL rdf:resource="https://doi.org/10.5281/zenodo.1305227"/> </dcat:Distribution> </dcat:distribution> <dcat:distribution> <dcat:Distribution> <dcat:accessURL rdf:resource="https://doi.org/10.5281/zenodo.1305227"/> <dcat:byteSize>26700459</dcat:byteSize> <dcat:downloadURL rdf:resource="https://zenodo.org/record/1305227/files/ZenodoPackage.zip"/> <dcat:mediaType>application/zip</dcat:mediaType> </dcat:Distribution> </dcat:distribution> </rdf:Description> </rdf:RDF>
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