Preparing an Incompressible-Flow Fluid Dynamics Code for Exascale-Class Wind Energy Simulations: Preprint

Paul Mullowney, Ruipeng Li, Stephen Thomas, Shreyas Ananthan, Ashesh Sharma, Jon Rood, Alan Williams, Michael Sprague

Research output: Contribution to conferencePaper

Abstract

The US Department of Energy has identified Exascale-Class wind farm simulation tools as critical to wind energy scientific discovery. A primary objective of the Exawind project is to build high-performance, predictive Computational Fluid Dynamics tools that satisfy these modeling needs. GPU accelerators will serve as the computational thoroughbreds of next generation, Exascale-Class, platforms. Here, we report on our efforts for preparing the Exawind unstructured mesh solver, Nalu-Wind, for Exascale-Class machines. For computing at this scale, a simple port of the incompressible-flow algorithms to GPUs is not sufficient. One needs novel algorithms that are application aware, memory efficient, and optimized for latest generation GPU devices to get high-performance. The result of our efforts are unstructured mesh simulations of wind turbines that use 1/6 the compute resources of Summit supercomputer at Oak Ridge National Lab. In particular, we demonstrate a first-of-its-kind, simulation using Algebraic Multigrid solvers on over 4000 GPUs.
Original languageAmerican English
Number of pages15
StatePublished - 2021
EventInternational Conference for High Performance Computing, Networking, Storage, and Analysis (SC21) -
Duration: 14 Nov 202119 Nov 2021

Conference

ConferenceInternational Conference for High Performance Computing, Networking, Storage, and Analysis (SC21)
Period14/11/2119/11/21

NREL Publication Number

  • NREL/CP-2C00-79645

Keywords

  • algebraic multigrid
  • CFD
  • computational linear algebra
  • exascale
  • GPU computing

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