{"title":"NVIDIA Deep Learning Tutorial","authors":"J. Bernauer","doi":"10.1109/IPDPS.2017.7","DOIUrl":null,"url":null,"abstract":"Learn how hardware and software stacks enable not only quick prototyping, but also efficient large-scale production deployments. The tutorial will conclude with a discussion about hands-on deep learning training opportunities as well as free academic teaching materials and GPU cloud platforms for university faculty.","PeriodicalId":209524,"journal":{"name":"2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPS.2017.7","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
Learn how hardware and software stacks enable not only quick prototyping, but also efficient large-scale production deployments. The tutorial will conclude with a discussion about hands-on deep learning training opportunities as well as free academic teaching materials and GPU cloud platforms for university faculty.