@misc{172c2a8f8f6b46e88be2e45be01fa736,
title = "Preparing an Incompressible-Flow Fluid Dynamics Code for Exascale-Class Wind Energy Simulations",
abstract = "The U.S. Department of Energy has identified exascale-class wind farm simulation as critical to wind energy scientific discovery. A primary objective of the ExaWind project is to build high-performance, predictive computational fluid dynamics (CFD) tools that satisfy these modeling needs. GPU accelerators will serve as the computational thoroughbreds of next-generation, exascale-class supercomputers. Here, we report on our efforts in 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 insufficient. To achieve high performance, one needs novel algorithms that are application aware, memory efficient, and optimized for the latest-generation GPU devices. The result of our efforts are unstructured-mesh simulations of wind turbines that can effectively leverage thousands of GPUs. In particular, we demonstrate a first-of-its-kind, incompressible-flow simulation using Algebraic Multigrid solvers that strong scales to more than 4000 GPUs on the Summit supercomputer.",
keywords = "algebraic multigrid, CFD, computational linear algebra, exascale, GPU computing",
author = "Paul Mullowney and Ruipeng Li and Stephen Thomas and Shreyas Ananthan and Ashesh Sharma and Jon Rood and Alan Williams and Michael Sprague",
year = "2021",
language = "American English",
series = "Presented at the International Conference for High Performance Computing, Networking, Storage, and Analysis, 14-19 November 2021, St. Louis, Missouri",
type = "Other",
}