{"title":"GPU Acceleration of CFD Simulations in OpenFOAM","authors":"Federico Piscaglia, F. Ghioldi","doi":"10.3390/aerospace10090792","DOIUrl":null,"url":null,"abstract":"We introduce algorithmic advancements designed to expedite simulations in OpenFOAM using GPUs. These developments include the following. (a) The amgx4Foam library, which connects the open-source AmgX library from NVIDIA to OpenFOAM. Matrix generation, involving tasks such numerical integration and assembly, is performed on CPUs. Subsequently, the assembled matrix is processed on the CPU. This approach accelerates the computationally intensive linear solver phase of simulations on GPUs. (b) Enhancements to code performance in reactive flow simulations, by relocating the solution of finite-rate chemistry to GPUs, which serve as co-processors. We present code verification and validation along with performance metrics targeting two distinct application sets, namely, aerodynamics calculations and supersonic combustion with finite-rate chemistry.","PeriodicalId":50845,"journal":{"name":"Aerospace America","volume":"33 1","pages":""},"PeriodicalIF":0.1000,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aerospace America","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3390/aerospace10090792","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, AEROSPACE","Score":null,"Total":0}
引用次数: 0
Abstract
We introduce algorithmic advancements designed to expedite simulations in OpenFOAM using GPUs. These developments include the following. (a) The amgx4Foam library, which connects the open-source AmgX library from NVIDIA to OpenFOAM. Matrix generation, involving tasks such numerical integration and assembly, is performed on CPUs. Subsequently, the assembled matrix is processed on the CPU. This approach accelerates the computationally intensive linear solver phase of simulations on GPUs. (b) Enhancements to code performance in reactive flow simulations, by relocating the solution of finite-rate chemistry to GPUs, which serve as co-processors. We present code verification and validation along with performance metrics targeting two distinct application sets, namely, aerodynamics calculations and supersonic combustion with finite-rate chemistry.