{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T14:11:51Z","timestamp":1781619111811,"version":"3.54.5"},"reference-count":12,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,3]]},"DOI":"10.23919\/date.2018.8342010","type":"proceedings-article","created":{"date-parts":[[2018,4,23]],"date-time":"2018-04-23T23:20:11Z","timestamp":1524525611000},"page":"241-244","source":"Crossref","is-referenced-by-count":30,"title":["SparseNN: An energy-efficient neural network accelerator exploiting input and output sparsity"],"prefix":"10.23919","author":[{"given":"Jingyang","family":"Zhu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingbo","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xizi","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chi-Ying","family":"Tsui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001138"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/nature16961"},{"key":"ref10","first-page":"242","article-title":"14.3 a 28nm soc with a 1.2 ghz 568nj\/prediction sparse deep-neural-network engine with > 0.1 timing error rate tolerance for iot applications","author":"whatmough","year":"2017","journal-title":"ISSCC"},{"key":"ref6","first-page":"581","article-title":"Lradnn: High-throughput and energy-efficient deep neural network accelerator using low rank approximation","author":"zhu","year":"2016","journal-title":"ASP-DAC"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273556"},{"key":"ref5","author":"han","year":"2015","journal-title":"Deep compression Compressing deep neural networks with pruning trained quantization and huffman coding"},{"key":"ref12","first-page":"22","author":"muralimanohar","year":"2009","journal-title":"CACTI 6 0 A Tool to Model Large Caches"},{"key":"ref8","author":"davis","year":"2013","journal-title":"Low-rank approximations for conditional feedforward computation in deep neural networks"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001163"},{"key":"ref2","first-page":"173","article-title":"Deep speech 2: End-to-end speech recognition in english and mandarin","author":"amodei","year":"2016","journal-title":"ICML"},{"key":"ref9","author":"courbariaux","year":"2016","journal-title":"Binarized neural networks Training deep neural networks with weights and activations constrained to+ l or-1"},{"key":"ref1","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"NIPS"}],"event":{"name":"2018 Design, Automation & Test in Europe Conference & Exhibition (DATE)","location":"Dresden, Germany","start":{"date-parts":[[2018,3,19]]},"end":{"date-parts":[[2018,3,23]]}},"container-title":["2018 Design, Automation & Test in Europe Conference & Exhibition (DATE)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8337149\/8341968\/08342010.pdf?arnumber=8342010","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,5,4]],"date-time":"2018-05-04T15:10:13Z","timestamp":1525446613000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/8342010\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,3]]},"references-count":12,"URL":"https:\/\/doi.org\/10.23919\/date.2018.8342010","relation":{},"subject":[],"published":{"date-parts":[[2018,3]]}}}