{"title":"1.1深度学习硬件:过去、现在和未来","authors":"Yann LeCun","doi":"10.1109/ISSCC.2019.8662396","DOIUrl":null,"url":null,"abstract":"Historically, progress in neural networks and deep learning research has been greatly influenced by the available hardware and software tools. This paper identifies trends in deep learning research that will influence hardware architectures and software platforms of the future.","PeriodicalId":265551,"journal":{"name":"2019 IEEE International Solid- State Circuits Conference - (ISSCC)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"89","resultStr":"{\"title\":\"1.1 Deep Learning Hardware: Past, Present, and Future\",\"authors\":\"Yann LeCun\",\"doi\":\"10.1109/ISSCC.2019.8662396\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Historically, progress in neural networks and deep learning research has been greatly influenced by the available hardware and software tools. This paper identifies trends in deep learning research that will influence hardware architectures and software platforms of the future.\",\"PeriodicalId\":265551,\"journal\":{\"name\":\"2019 IEEE International Solid- State Circuits Conference - (ISSCC)\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"89\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE International Solid- State Circuits Conference - (ISSCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSCC.2019.8662396\",\"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 International Solid- State Circuits Conference - (ISSCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSCC.2019.8662396","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
1.1 Deep Learning Hardware: Past, Present, and Future
Historically, progress in neural networks and deep learning research has been greatly influenced by the available hardware and software tools. This paper identifies trends in deep learning research that will influence hardware architectures and software platforms of the future.