Resolved particle simulations using the Physalis method on many GPUs.

We present a distributed memory many-GPU implementation of the Physalis method for resolving spherical particles in disperse multiphase flow simulations. The current work extends a previous single-GPU computational procedure by implementing a distributed memory Poisson solver and distributed finite-size particle methods using MPI. We document the changes required to move to a distributed memory model for both the fluid and solid phases. We benchmark the code with up to one million resolved particles in a domain size of 192 0 3 on 216 GPUs at the Maryland Advanced Research Computing Center and present strong and weak scaling results. Finally, by taking advantage of the realization that the solution procedure for the pressure Poisson equation can be implemented using a symmetric matrix, we are able to replace the biconjugate gradient stabilized algorithm used in previous work with the conjugate gradient algorithm. • We present a many-GPU implementation of the Physalis method for resolved particle-laden flows. • The implementation uses MPI to distribute fluid and particle memory among GPUs. • We benchmark the strong and weak scaling performance of the code with up to one million resolved particles on 216 GPUs at the Maryland Advanced Research Computing Center. [ABSTRACT FROM AUTHOR]