Anuva Kulkarni, Daniele G. Spampinato, F. Franchetti
{"title":"微机械应力-应变分析FFTX","authors":"Anuva Kulkarni, Daniele G. Spampinato, F. Franchetti","doi":"10.1109/HPEC.2019.8916267","DOIUrl":null,"url":null,"abstract":"Porting scientific simulations to heterogeneous platforms requires complex algorithmic and optimization strategies to overcome memory and communication bottlenecks. Such operations are inexpressible using traditional libraries (e.g., FFTW for spectral methods) and difficult to optimize by hand for various hardware platforms. In this work, we use our GPU-adapted stress-strain analysis method to show how FFTX, a new API that extends FFTW, can be used to express our algorithm without worrying about code optimization, which is handled by a backend code generator.","PeriodicalId":184253,"journal":{"name":"2019 IEEE High Performance Extreme Computing Conference (HPEC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"FFTX for Micromechanical Stress-Strain Analysis\",\"authors\":\"Anuva Kulkarni, Daniele G. Spampinato, F. Franchetti\",\"doi\":\"10.1109/HPEC.2019.8916267\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Porting scientific simulations to heterogeneous platforms requires complex algorithmic and optimization strategies to overcome memory and communication bottlenecks. Such operations are inexpressible using traditional libraries (e.g., FFTW for spectral methods) and difficult to optimize by hand for various hardware platforms. In this work, we use our GPU-adapted stress-strain analysis method to show how FFTX, a new API that extends FFTW, can be used to express our algorithm without worrying about code optimization, which is handled by a backend code generator.\",\"PeriodicalId\":184253,\"journal\":{\"name\":\"2019 IEEE High Performance Extreme Computing Conference (HPEC)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE High Performance Extreme Computing Conference (HPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPEC.2019.8916267\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE High Performance Extreme Computing Conference (HPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPEC.2019.8916267","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Porting scientific simulations to heterogeneous platforms requires complex algorithmic and optimization strategies to overcome memory and communication bottlenecks. Such operations are inexpressible using traditional libraries (e.g., FFTW for spectral methods) and difficult to optimize by hand for various hardware platforms. In this work, we use our GPU-adapted stress-strain analysis method to show how FFTX, a new API that extends FFTW, can be used to express our algorithm without worrying about code optimization, which is handled by a backend code generator.