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.
| Original language | American English |
|---|---|
| Number of pages | 19 |
| State | Published - 2021 |
Publication series
| Name | Presented at the International Conference for High Performance Computing, Networking, Storage, and Analysis, 14-19 November 2021, St. Louis, Missouri |
|---|
NLR Publication Number
- NREL/PR-2C00-81212
Keywords
- algebraic multigrid
- CFD
- computational linear algebra
- exascale
- GPU computing
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