{"title":"From Parallelization to Customization – Challenges and Opportunities","authors":"J. Cong","doi":"10.1109/IPDPS49936.2021.00077","DOIUrl":null,"url":null,"abstract":"With large-scale deployment of FPGAs in both private and public clouds in the past a few years, customizable computing is transitioning from advanced research into mainstream computing. In this talk, I shall first showcase a few big data and machine learning applications that benefit significantly from customization. Next, I shall discuss the challenges of FPGA programming for the efficient accelerator designs, which presents a significant barrier to many software programmers, despite the recent advances in high-level synthesis. Then, I shall highlight our recent progress on automated compilation for customized archictectures, such as systolic arrays, stencils, and more general CPPs (composable parallel and pipelined) architectures. I shall also present our ongoing work on HeteroCL, a highly productive multi-paradigm programming framework targeting accelerator-rich heterogeneous architectures, and is being used as a focal point to integrate various optimizaiton techniques and support high-level domain-specific languages (DSL) such as Halide and Pytorch. Our goal is to “demacratize customizable computing” so that most (if not all) software programmers can design optimized accelerators on FPGAs.","PeriodicalId":372234,"journal":{"name":"2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPS49936.2021.00077","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
With large-scale deployment of FPGAs in both private and public clouds in the past a few years, customizable computing is transitioning from advanced research into mainstream computing. In this talk, I shall first showcase a few big data and machine learning applications that benefit significantly from customization. Next, I shall discuss the challenges of FPGA programming for the efficient accelerator designs, which presents a significant barrier to many software programmers, despite the recent advances in high-level synthesis. Then, I shall highlight our recent progress on automated compilation for customized archictectures, such as systolic arrays, stencils, and more general CPPs (composable parallel and pipelined) architectures. I shall also present our ongoing work on HeteroCL, a highly productive multi-paradigm programming framework targeting accelerator-rich heterogeneous architectures, and is being used as a focal point to integrate various optimizaiton techniques and support high-level domain-specific languages (DSL) such as Halide and Pytorch. Our goal is to “demacratize customizable computing” so that most (if not all) software programmers can design optimized accelerators on FPGAs.