367838 Scalable Monte Carlo Simulations of Millions of Particles on Thousands of GPUs

Tuesday, November 18, 2014: 3:15 PM
212 (Hilton Atlanta)
Joshua A. Anderson1, M. Eric Irrgang2 and Sharon C. Glotzer1, (1)Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, (2)Materials Science and Engineering, University of Michigan Ann Arbor, Ann Arbor, MI

We develop a scalable parallel algorithm for Metropolis Monte Carlo simulations of particles with short-range interactions. We use a checkerboard decomposition to allow massively parallel trial moves on GPUs. A second level of domain decomposition enables scaling to systems of millions of particles on thousands of GPUs. A CPU code path efficiently scales to thousands of CPU cores, with as few as one hundred particles per rank. We implement this algorithm for hard anisotropic particles as a plugin to our open-source particle simulation toolkit HOOMD-blue (http://codeblue.umich.edu/hoomd-blue). Our implementation is production-ready with all the features needed for general use in a large research group. It supports a variety of shapes (spheres, ellipsoids, convex (sphero)polygons, simple polygons, convex (sphero)polyhedra, and general polyhedra), NVT and NPT ensembles, pressure measurement, and free energy calculations along with all the file I/O and scripting capabilities already present in HOOMD-blue.

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