{"title":"DeepPump: Multi-pumping deep Neural Networks","authors":"Ruizhe Zhao, T. Todman, W. Luk, Xinyu Niu","doi":"10.1109/ASAP.2017.7995281","DOIUrl":null,"url":null,"abstract":"This paper presents DeepPump, an approach that generates CNN hardware designs with multi-pumping, which have competitive performance when compared with previous designs. Future work includes integrating DeepPump with other optimisations, and providing further evaluations on various FPGA platforms.","PeriodicalId":405953,"journal":{"name":"2017 IEEE 28th International Conference on Application-specific Systems, Architectures and Processors (ASAP)","volume":"296 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 28th International Conference on Application-specific Systems, Architectures and Processors (ASAP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASAP.2017.7995281","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper presents DeepPump, an approach that generates CNN hardware designs with multi-pumping, which have competitive performance when compared with previous designs. Future work includes integrating DeepPump with other optimisations, and providing further evaluations on various FPGA platforms.