{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T00:59:34Z","timestamp":1725584374770},"reference-count":23,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"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":[[2020,8]]},"DOI":"10.1109\/aicas48895.2020.9073832","type":"proceedings-article","created":{"date-parts":[[2020,4,24]],"date-time":"2020-04-24T01:16:57Z","timestamp":1587691017000},"page":"315-319","source":"Crossref","is-referenced-by-count":0,"title":["Exploiting Variable Precision Computation Array for Scalable Neural Network Accelerators"],"prefix":"10.1109","author":[{"given":"Shaofei","family":"Yang","sequence":"first","affiliation":[]},{"given":"Longjun","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Baoting","family":"Li","sequence":"additional","affiliation":[]},{"given":"Hongbin","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Nanning","family":"Zheng","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3037697.3037702"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001179"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO.2016.7783720"},{"key":"ref13","article-title":"Cnvlutin: ineffectual-activation-free deep neural network computing","author":"albericio","year":"2016","journal-title":"ISCA"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001139"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3079856.3080254"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3061639.3062189"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001177"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3079856.3080246"},{"key":"ref19","article-title":"Quantized neural networks: Training neural networks with low precision weights and activations","author":"hubara","year":"2016","journal-title":"arXiv preprint arXiv 1609 04802"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3195970.3196072"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/LCA.2016.2597140"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/2541940.2541967"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ISCA.2018.00069"},{"key":"ref8","article-title":"Unpu: A 50.6 tops\/w unified deep neural network accelerator with 1b-to-16b fullyvariable weight bit-precision","author":"lee","year":"2018","journal-title":"ISSCC"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001163"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO.2014.58"},{"key":"ref1","article-title":"Reduced Precision Strategies for Bounded Memory in Deep Neural Nets","author":"judd","year":"2015","journal-title":"arXiv preprint arXiv 1511 05271"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ISVLSI.2016.111"},{"key":"ref20","article-title":"DoReFaNet: Training low bitwidth convolutional neural networks with low bitwidth gradients","author":"zhou","year":"2016","journal-title":"arXiv preprint arXiv 1606 06160"},{"key":"ref22","article-title":"Ternary weight networks","author":"li","year":"2016","journal-title":"ArXiv"},{"key":"ref21","article-title":"WRPN: wide reduced-precision networks","author":"mishra","year":"2017","journal-title":"ArXiv"},{"key":"ref23","article-title":"Xnor-net: Imagenet classification using binary convolutional neural networks","author":"rastegari","year":"2016","journal-title":"ArXiv"}],"event":{"name":"2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)","start":{"date-parts":[[2020,8,31]]},"location":"Genova, Italy","end":{"date-parts":[[2020,9,2]]}},"container-title":["2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9066468\/9072687\/09073832.pdf?arnumber=9073832","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T15:45:38Z","timestamp":1656344738000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9073832\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1109\/aicas48895.2020.9073832","relation":{},"subject":[],"published":{"date-parts":[[2020,8]]}}}