{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T19:00:08Z","timestamp":1771700408754,"version":"3.50.1"},"reference-count":69,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100013290","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFA0700900"],"award-info":[{"award-number":["2017YFA0700900"]}],"id":[{"id":"10.13039\/501100013290","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013290","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFA0700902"],"award-info":[{"award-number":["2017YFA0700902"]}],"id":[{"id":"10.13039\/501100013290","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013290","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFA0700901"],"award-info":[{"award-number":["2017YFA0700901"]}],"id":[{"id":"10.13039\/501100013290","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013290","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFB1003101"],"award-info":[{"award-number":["2017YFB1003101"]}],"id":[{"id":"10.13039\/501100013290","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013290","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018AAA0103300"],"award-info":[{"award-number":["2018AAA0103300"]}],"id":[{"id":"10.13039\/501100013290","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61432016"],"award-info":[{"award-number":["61432016"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61532016"],"award-info":[{"award-number":["61532016"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61672491"],"award-info":[{"award-number":["61672491"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61602441"],"award-info":[{"award-number":["61602441"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61602446"],"award-info":[{"award-number":["61602446"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61732002"],"award-info":[{"award-number":["61732002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61702478"],"award-info":[{"award-number":["61702478"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61732007"],"award-info":[{"award-number":["61732007"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61732020"],"award-info":[{"award-number":["61732020"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","award":["JQ18013"],"award-info":[{"award-number":["JQ18013"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]},{"name":"973 Program of China","award":["2015CB358800"],"award-info":[{"award-number":["2015CB358800"]}]},{"name":"National Science and Technology Major Project","award":["2018ZX01031102"],"award-info":[{"award-number":["2018ZX01031102"]}]},{"name":"Transformation and Transfer of Scientific and Technological Achievements of Chinese Academy of Sciences","award":["KFJ-HGZX-013"],"award-info":[{"award-number":["KFJ-HGZX-013"]}]},{"name":"Key Research Projects in Frontier Science of Chinese Academy of Sciences","award":["QYZDB-SSW-JSC001"],"award-info":[{"award-number":["QYZDB-SSW-JSC001"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Science","award":["XDB32050200"],"award-info":[{"award-number":["XDB32050200"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Science","award":["XDC01020000"],"award-info":[{"award-number":["XDC01020000"]}]},{"name":"Standardization Research Project of Chinese Academy of Sciences","award":["BZ201800001"],"award-info":[{"award-number":["BZ201800001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Comput."],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/tc.2020.2978475","type":"journal-article","created":{"date-parts":[[2020,3,6]],"date-time":"2020-03-06T00:54:36Z","timestamp":1583456076000},"page":"1-1","source":"Crossref","is-referenced-by-count":7,"title":["Addressing Irregularity in Sparse Neural Networks through a Cooperative Software\/Hardware Approach"],"prefix":"10.1109","author":[{"given":"Xi","family":"Zeng","sequence":"first","affiliation":[]},{"given":"Xuehai","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Ling","family":"Li","sequence":"additional","affiliation":[]},{"given":"Tianshi","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Ninghui","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Yunji","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Tian","family":"Zhi","sequence":"additional","affiliation":[]},{"given":"Xuda","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Zidong","family":"Du","sequence":"additional","affiliation":[]},{"given":"Qi","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Shaoli","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Bingrui","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yuanbo","family":"Wen","sequence":"additional","affiliation":[]},{"given":"Chao","family":"Wang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","article-title":"cuda-convnet: High-performance C++\/CUDA implementation of convolutional neural networks","volume":"7","author":"krizhevsky","year":"2012"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref33","doi-asserted-by":"crossref","DOI":"10.1515\/9780691213866","author":"henneaux","year":"1992","journal-title":"Quantization of Gauge Systems"},{"key":"ref32","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2015"},{"key":"ref31","article-title":"Efficient sparse coding algorithms","volume":"19","author":"lee","year":"2007","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref30","first-page":"873","article-title":"Sparse deep belief net model for visual area V2","author":"lee","year":"2008","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref37","article-title":"Coded representation of picture and audio informationprogressive bi-level lmage compression standard","year":"1990"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2016.2616357"},{"key":"ref35","first-page":"253","article-title":"CNNPack: Packing convolutional neural networks in the frequency domain","author":"wang","year":"2016","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref34","author":"mackay","year":"2003","journal-title":"Information Theory Inference and Learning Algorithms"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/ICNN.1993.298572"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2011.5981829"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1145\/3289602.3293898"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1145\/1815961.1815993"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1038\/381607a0"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1145\/3079856.3080215"},{"key":"ref27","volume":"1","author":"pratt","year":"1989","journal-title":"ch Comparing Biases for Minimal Network Construction with Back-propagation"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1145\/3123939.3123970"},{"key":"ref66","first-page":"2074","article-title":"Learning structured sparsity in deep neural networks","author":"wen","year":"2016","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref29","first-page":"1185","article-title":"Sparse feature learning for deep belief networks","author":"boureau","year":"2008","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.280"},{"key":"ref68","article-title":"Pruning filters for efficient convnets","author":"li","year":"0"},{"key":"ref69","article-title":"Exploring the regularity of sparse structure in convolutional neural networks","author":"mao","year":"0"},{"key":"ref2","first-page":"173","article-title":"Deep speech 2: End-to-end speech recognition in english and mandarin","author":"amodei","year":"2016"},{"key":"ref1","first-page":"567","article-title":"Learning to label aerial images from noisy data","author":"mnih","year":"2012","journal-title":"Proc 29th Int Conf Mach Learn"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3020078.3021745"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3352460.3358291"},{"key":"ref21","first-page":"27","article-title":"SCNN: An accelerator for compressed-sparse convolutional neural networks","author":"angshuman","year":"2017","journal-title":"Proc 44th Annu Int Symp Comput Archit"},{"key":"ref24","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"J Mach Learn Res"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/JETCAS.2019.2910232"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/502059.502044"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/2627369.2627613"},{"key":"ref50","first-page":"4171","article-title":"Bert: Pre-training of deep bidirectional transformers for language understanding","volume":"1","author":"devlin","year":"2019"},{"key":"ref51","article-title":"Compressing deep convolutional networks using vector quantization","author":"gong","year":"0"},{"key":"ref59","first-page":"598","article-title":"Optimal brain damage","volume":"2","author":"lecun","year":"1989","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref58","article-title":"Diversity networks","author":"mariet","year":"0"},{"key":"ref57","article-title":"Network trimming: A data-driven neuron pruning approach towards efficient deep architectures","author":"hu","year":"0","journal-title":"CoRR"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.5244\/C.29.31"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2014.6853595"},{"key":"ref54","first-page":"1269","article-title":"Exploiting linear structure within convolutional networks for efficient evaluation","author":"denton","year":"2014","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref53","first-page":"2285","article-title":"Compressing neural networks with the hashing trick","author":"chen","year":"2015","journal-title":"Proc 32nd Int Conf Mach Learn"},{"key":"ref52","first-page":"4107","article-title":"Binarized neural networks","author":"hubara","year":"2016"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6639343"},{"key":"ref11","first-page":"1337","article-title":"Deep learning with COTS HPC systems","author":"coates","year":"2013","journal-title":"Proc 30th Int Conf Mach Learn"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref12","first-page":"1135","article-title":"Learning both weights and connections for efficient neural network","author":"han","year":"2015","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref13","article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding","author":"han","year":"2016"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/12.210171"},{"key":"ref15","first-page":"525","article-title":"XNOR-Net: ImageNet classification using binary convolutional neural networks","author":"rastegari","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO.2016.7783723"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001138"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001163"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO.2018.00024"},{"key":"ref4","article-title":"Very deep convolutional networks for natural language processing","volume":"abs 1606 1781","author":"conneau","year":"2016"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6639215"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO.2014.58"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/2541940.2541967"},{"key":"ref8","first-page":"513","article-title":"DLAU: A scalable deep learning accelerator unit on FPGA","volume":"36","author":"wang","year":"2017","journal-title":"IEEE Trans Comput -Aided Des Integr Circuits Syst"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2872887.2750389"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/MC.1984.1659158"},{"key":"ref9","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2015.7178964"},{"key":"ref45","article-title":"The NVIDIA cuda sparse matrix library (cuSPARSE)","year":"0"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1978.1055934"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/JRPROC.1952.273898"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO.2007.33"},{"key":"ref41","first-page":"338","article-title":"Long short-term memory recurrent neural network architectures for large scale acoustic modeling","author":"sak","year":"2014","journal-title":"Proc Annu Conf Int Speech Commun Assoc"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/567806.567810"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2654889"}],"container-title":["IEEE Transactions on Computers"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/12\/4358213\/09025249.pdf?arnumber=9025249","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T14:16:12Z","timestamp":1651068972000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9025249\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":69,"URL":"https:\/\/doi.org\/10.1109\/tc.2020.2978475","relation":{},"ISSN":["0018-9340","1557-9956","2326-3814"],"issn-type":[{"value":"0018-9340","type":"print"},{"value":"1557-9956","type":"electronic"},{"value":"2326-3814","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}