@article{dd782e476618444f86c63c48d968100d,
title = "Efficient mesoscale hydrodynamics: Multiparticle collision dynamics with massively parallel GPU acceleration",
abstract = "We present an efficient open-source implementation of the multiparticle collision dynamics (MPCD) algorithm that scales to run on hundreds of graphics processing units (GPUs). We especially focus on optimizations for modern GPU architectures and communication patterns between multiple GPUs. We show that a mixed-precision computing model can improve performance compared to a fully double-precision model while still providing good numerical accuracy. We report weak and strong scaling benchmarks of a reference MPCD solvent and a benchmark of a polymer solution with research-relevant interactions and system size. Our MPCD software enables simulations of mesoscale hydrodynamics at length and time scales that would be otherwise challenging or impossible to access.",
keywords = "GPU, Hybrid simulations, MPI, Mesoscale hydrodynamics, Molecular dynamics, Multiparticle collision dynamics",
author = "Howard, {Michael P.} and Panagiotopoulos, {Athanassios Z.} and Arash Nikoubashman",
note = "Funding Information: This research is part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (awards OCI-0725070 and ACI-1238993 ) and the state of Illinois . Blue Waters is a joint effort of the University of Illinois at Urbana–Champaign and its National Center for Supercomputing Applications. Additional financial support for this work was provided by the Princeton Center for Complex Materials, U.S. National Science Foundation Materials Research Science and Engineering Center (award DMR-1420541 ), and the German Research Foundation under project number NI 1487/2-1 . We gratefully acknowledge use of computational resources supported by the Princeton Institute for Computational Science and Engineering and the Office of Information Technology{\textquoteright}s High Performance Computing Center and Visualization Laboratory at Princeton University. Publisher Copyright: {\textcopyright} 2018 Elsevier B.V.",
year = "2018",
month = sep,
doi = "10.1016/j.cpc.2018.04.009",
language = "English (US)",
volume = "230",
pages = "10--20",
journal = "Computer Physics Communications",
issn = "0010-4655",
publisher = "Elsevier",
}