{"title":"fpga在深度学习中的作用","authors":"A. Ling, J. Anderson","doi":"10.1145/3020078.3030013","DOIUrl":null,"url":null,"abstract":"Deep learning has garnered significant visibility recently as an Artificial Intelligence (AI) paradigm, with success in wide ranging applications such as image and speech recognition, natural language understanding, self-driving cars, and game playing (e.g., Alpha Go). This special session is devoted to exploring the potential role of FPGAs in this important fast-evolving domain.","PeriodicalId":252039,"journal":{"name":"Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"The Role of FPGAs in Deep Learning\",\"authors\":\"A. Ling, J. Anderson\",\"doi\":\"10.1145/3020078.3030013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Deep learning has garnered significant visibility recently as an Artificial Intelligence (AI) paradigm, with success in wide ranging applications such as image and speech recognition, natural language understanding, self-driving cars, and game playing (e.g., Alpha Go). This special session is devoted to exploring the potential role of FPGAs in this important fast-evolving domain.\",\"PeriodicalId\":252039,\"journal\":{\"name\":\"Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3020078.3030013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3020078.3030013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Deep learning has garnered significant visibility recently as an Artificial Intelligence (AI) paradigm, with success in wide ranging applications such as image and speech recognition, natural language understanding, self-driving cars, and game playing (e.g., Alpha Go). This special session is devoted to exploring the potential role of FPGAs in this important fast-evolving domain.
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