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

التفاصيل البيبلوغرافية
العنوان: Preparing an Incompressible-Flow Fluid Dynamics Code for Exascale-Class Wind Energy Simulations
المؤلفون: Michael A. Sprague, Shreyas Ananthan, Ruipeng Li, Paul Mullowney, Stephen Thomas, Ashesh Sharma, Jon Rood, Alan B. Williams
المصدر: SC
بيانات النشر: US DOE, 2021.
سنة النشر: 2021
مصطلحات موضوعية: Wind power, ComputerSystemsOrganization_COMPUTERSYSTEMIMPLEMENTATION, business.industry, Computer science, Computational fluid dynamics, Solver, Supercomputer, Computational science, Computer Science::Performance, Multigrid method, Computer Science::Mathematical Software, Fluid dynamics, Leverage (statistics), General-purpose computing on graphics processing units, business, ComputingMethodologies_COMPUTERGRAPHICS
الوصف: 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.
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45eb09494f79f0506b699d4c2e22e411
https://doi.org/10.2172/1891739
حقوق: OPEN
رقم الأكسشن: edsair.doi.dedup.....45eb09494f79f0506b699d4c2e22e411
قاعدة البيانات: OpenAIRE