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Pushing the frontiers of polymer simulation with texture memory

Airidas Korolkovas

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  <identifier identifierType="DOI">10.5281/zenodo.1305227</identifier>
      <creatorName>Airidas Korolkovas</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0001-7904-5639</nameIdentifier>
      <affiliation>Uppsala University</affiliation>
    <title>Pushing the frontiers of polymer simulation with texture memory</title>
    <subject>GPU, CUDA, textures, polymers, entanglement, reptation</subject>
    <date dateType="Issued">2018-07-04</date>
  <resourceType resourceTypeGeneral="Software"/>
    <alternateIdentifier alternateIdentifierType="url"></alternateIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsCitedBy"></relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsCitedBy">10.1002/adts.201800078</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.1305226</relatedIdentifier>
    <rights rightsURI="">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;Pushing the frontiers of polymer simulation with texture memory&lt;br&gt;

Welcome to the Source Code for simulating entangled star polymers.&lt;br&gt;
This custom software was used to generate data for the article &amp;ldquo;Five dimensional entanglement in star polymer dynamics&amp;quot;&lt;br&gt;
published in Advanced Theory and Simulations (Wiley)&lt;br&gt;
A preprint is available here:;/p&gt;

&lt;p&gt;The demo provided here simulates Brownian dynamics of NS=104 stars with 3 arms, of length N=356 beads per arm.&lt;br&gt;
It requires a CUDA-enabled GPU card, which is managed from a Matlab environment using the launchstars.m script.&lt;br&gt;
The .cu source files are included and have been pre-compiled for several star sizes using this command:&lt;br&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; mexcuda;/p&gt;

&lt;p&gt;Now simply run:&lt;br&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; launchstars.m&lt;/p&gt;

&lt;p&gt;The default settings create the initial polymer configuration in Matlab, which is then transferred to GPU and processed by CUDA for 1000 steps.&lt;br&gt;
The resulting configuration is returned to Matlab, and selected data is stored for later analysis.&lt;br&gt;
This cycle is repeated 200 times, and the real-space configuration is optionally plotted in 3D (see a snapshot in the Figures folder).&lt;br&gt;
Once the demo is complete, you may verify the speed of the computation using this command (it runs an extra numIterations=1000 steps):&lt;/p&gt;

&lt;p&gt;&amp;nbsp;&amp;nbsp; &amp;nbsp;tic; [R, randvector, ~] = fh(single(gpuArray(R)), randvector, b, vstrong, rstrong, cosbeta, numIterations, timeStep); toc;&lt;br&gt;
&amp;nbsp;&amp;nbsp; &amp;nbsp;Elapsed time is 0.398752 seconds.&lt;/p&gt;

&lt;p&gt;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.&lt;br&gt;
The whole demo lasts about 1 minute 30 seconds.&lt;br&gt;
The branch point trajectory may be analysed by running the script autodiff.m provided in the Data Analysis Tools folder.&lt;br&gt;
A typical result is shown in the MSD.pdf figure. Sub-reptative behaviour (negative slope) is apparent within one minute of simulation.&lt;/p&gt;

Airidas Korolkovas, PhD&lt;br&gt;
Institut Laue-Langevin&lt;br&gt;
Uppsala University&lt;br&gt;;br&gt;;/p&gt;

&lt;p&gt;July 04, 2018&lt;/p&gt;</description>
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