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Pushing the frontiers of polymer simulation with texture memory

Airidas Korolkovas


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        <foaf:name>Airidas Korolkovas</foaf:name>
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    <dct:title>Pushing the frontiers of polymer simulation with texture memory</dct:title>
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    <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>
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    <dct:description>&lt;p&gt;Pushing the frontiers of polymer simulation with texture memory&lt;br&gt; ---------------------------------------------------------------&lt;/p&gt; &lt;p&gt;&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: https://arxiv.org/abs/1805.08508&lt;/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 mystar356.cu&lt;/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; &lt;p&gt;&lt;br&gt; Author:&lt;br&gt; Airidas Korolkovas, PhD&lt;br&gt; Institut Laue-Langevin&lt;br&gt; Uppsala University&lt;br&gt; korolkovas@ill.fr&lt;br&gt; airidas.korolkovas89@gmail.com&lt;/p&gt; &lt;p&gt;July 04, 2018&lt;/p&gt;</dct:description>
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