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Parallel Optimization Methods for Direct Numerical Simulation of High Reynolds Number Wall Turbulence with a Grid Size of 100 Billion
DescriptionDirect numerical simulation (DNS) is a technique that directly solves the fluid Navier-Stokes equations with high spatial and temporal resolutions. However, its utility in studying high Reynolds number (Re) wall turbulence of particular interest is limited by the rapidly growing grid size (i.e., the memory and computation requirement) with Re^3.

We present PowerLLEL, a high-performance finite difference solver tailored for the challenging DNS of incompressible wall turbulence at extreme scales. An adaptive multi-level parallelization strategy is proposed to fully exploit the multi-level parallelism of various architectures and enhance computational performance. The communication performance of global transpose and halo exchange is significantly improved by a tridiagonal solver based on the parallel diagonal dominant (PDD) algorithm and three RDMA-implemented communication optimizations. Strong scaling tests on the Tianhe-2A supercomputer show that PowerLLEL achieves nearly 92% parallel efficiency with up to 31,104 cores on a grid size of 143.3 billion.
Event Type
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Research Posters
TimeTuesday, 14 November 202310am - 5pm MST
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