{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T18:41:00Z","timestamp":1725734460525},"reference-count":19,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,7]]},"DOI":"10.1109\/dac18072.2020.9218518","type":"proceedings-article","created":{"date-parts":[[2020,10,9]],"date-time":"2020-10-09T15:57:03Z","timestamp":1602259023000},"page":"1-6","source":"Crossref","is-referenced-by-count":4,"title":["Convergence-Aware Neural Network Training"],"prefix":"10.1109","author":[{"given":"Hyungjun","family":"Oh","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongseung","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giha","family":"Ryu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gunjoo","family":"Ahn","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuri","family":"Jeong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongjun","family":"Park","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiwon","family":"Seo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"crossref","DOI":"10.1145\/3065386","article-title":"Imagenet classification with deep convolutional neural networks","volume-title":"NeurIPS","author":"Krizhevsky"},{"article-title":"Bert: Pre-training of deep bidirectional transformers for language understanding","year":"2018","author":"Devlin","key":"ref2"},{"article-title":"Layer-wise performance bottleneck analysis of deep neural networks","volume-title":"The 1st International Workshop on Architectures for Intelligent Machine","author":"Zhao","key":"ref3"},{"article-title":"Tensorflow: A system for large-scale machine learning","volume-title":"USENIX OSDI","author":"Abadi","key":"ref4"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001165"},{"article-title":"Mixed precision training of convolutional neural networks using integer operations","year":"2018","author":"Das","key":"ref7"},{"article-title":"Qsgd: Communication-efficient sgd via gradient quantization and encoding","volume-title":"NeurIPS","author":"Alistarh","key":"ref8"},{"article-title":"Dorefa-net: Training low bitwidth convolutional neural networks with low bitwidth gradients","year":"2016","author":"Zhou","key":"ref9"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2011.311"},{"article-title":"Looknn: Neural network with no multiplication","year":"2017","author":"Samragh","key":"ref11"},{"article-title":"The MNIST database of handwritten digits","year":"1998","author":"LeCun","key":"ref12"},{"article-title":"Reading digits in natural images with unsupervised feature learning","volume-title":"NeurIPS Workshop","author":"Netzer","key":"ref13"},{"article-title":"Learning multiple layers of features from tiny images","year":"2009","author":"Krizhevsky","key":"ref14"},{"article-title":"Sparse communication for distributed gradient descent","volume-title":"ACL EMNLP","author":"Fikri Aji","key":"ref15"},{"article-title":"Deep gradient compression: Reducing the communication bandwidth for distributed training","year":"2017","author":"Lin","key":"ref16"},{"article-title":"Terngrad: Ternary gradients to reduce communication in distributed deep learning","volume-title":"NuerIPS","author":"Wen","key":"ref17"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/1248377.1248389"},{"article-title":"Best-effort parallel execution framework for recognition and mining applications","volume-title":"IEEE ISPA","author":"Meng","key":"ref19"}],"event":{"name":"2020 57th ACM\/IEEE Design Automation Conference (DAC)","start":{"date-parts":[[2020,7,20]]},"location":"San Francisco, CA, USA","end":{"date-parts":[[2020,7,24]]}},"container-title":["2020 57th ACM\/IEEE Design Automation Conference (DAC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9211868\/9218488\/09218518.pdf?arnumber=9218518","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T20:11:46Z","timestamp":1706040706000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9218518\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7]]},"references-count":19,"URL":"https:\/\/doi.org\/10.1109\/dac18072.2020.9218518","relation":{},"subject":[],"published":{"date-parts":[[2020,7]]}}}