{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T17:58:47Z","timestamp":1772906327741,"version":"3.50.1"},"reference-count":44,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2017,4,1]],"date-time":"2017-04-01T00:00:00Z","timestamp":1491004800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"name":"Research Foundation \u2013 Flanders"},{"DOI":"10.13039\/100002418","name":"Intel Corporation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100002418","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Solid-State Circuits"],"published-print":{"date-parts":[[2017,4]]},"DOI":"10.1109\/jssc.2016.2636225","type":"journal-article","created":{"date-parts":[[2016,12,29]],"date-time":"2016-12-29T19:23:23Z","timestamp":1483039403000},"page":"903-914","source":"Crossref","is-referenced-by-count":174,"title":["An Energy-Efficient Precision-Scalable ConvNet Processor in 40-nm CMOS"],"prefix":"10.1109","volume":"52","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0136-8232","authenticated-orcid":false,"given":"Bert","family":"Moons","sequence":"first","affiliation":[]},{"given":"Marian","family":"Verhelst","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ISLPED.2015.7273520"},{"key":"ref38","first-page":"248","article-title":"ImageNet: A large-scale hierarchical image database","author":"deng","year":"2009","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref33","first-page":"1","article-title":"A 0.3&#x2013;2.6 TOPS\/W precision-scalable processor for real-time large-scale ConvNets","author":"moons","year":"2016","journal-title":"Proc IEEE Symp VLSI Circuits"},{"key":"ref32","first-page":"267","article-title":"Minerva: Enabling low-power, highly-accurate deep neural network accelerators","author":"reagen","year":"2016","journal-title":"Proc ACM\/IEEE 43rd Annu Int Symp Comput Archit (ISCA)"},{"key":"ref31","first-page":"243","article-title":"EIE: Efficient inference engine on compressed deep neural network","author":"han","year":"2016","journal-title":"Proc ACM\/IEEE 43rd Annu Int Symp Comput Archi (ISCA)"},{"key":"ref30","first-page":"1","article-title":"Cnvlutin: Ineffectual-neuron-free deep neural network computing","author":"albericio","year":"2016","journal-title":"Proc ACM\/IEEE 43rd Annu Int Symp Comput Archit (ISCA)"},{"key":"ref37","author":"lecun","year":"1998","journal-title":"The MNIST Database of Handwritten Digits"},{"key":"ref36","article-title":"Deep compression: Compressing deep neural network with pruning, trained quantization and Huffman coding","volume":"abs 1510 149","author":"han","year":"2016","journal-title":"CoRR"},{"key":"ref35","article-title":"Gradient flow in recurrent nets: The difficulty of learning long-term dependencies","author":"hochreiter","year":"2001","journal-title":"A Field Guide to Dynamical Recurrent Networks"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ACSSC.2013.6810241"},{"key":"ref10","first-page":"91","article-title":"Faster R-CNN: Towards real-time object detection with region proposal networks","author":"ren","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/4.881202"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298878"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCD.2013.6657019"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2016.7477614"},{"key":"ref15","article-title":"Binarized neural networks: Training deep neural networks with weights and activations constrained to +1 or ?1","author":"courbariaux","year":"2016"},{"key":"ref16","article-title":"Hardware-oriented approximation of convolutional neural networks","volume":"abs 1604 3168","author":"gysel","year":"2016","journal-title":"CoRR"},{"key":"ref17","article-title":"Resiliency of deep neural networks under quantization","author":"sung","year":"2015"},{"key":"ref18","article-title":"SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size","author":"iandola","year":"2016"},{"key":"ref19","first-page":"1135","article-title":"Learning both weights and connections for efficient neural network","author":"han","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/2749469.2750389"},{"key":"ref4","first-page":"1058","article-title":"Regularization of neural networks using dropconnect","author":"wan","year":"2013","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO.2014.58"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref6","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/2742060.2743766"},{"key":"ref5","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2012.6288864"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref20","article-title":"Improving the speed of neural networks on CPUs","author":"vanhoucke","year":"2011","journal-title":"Proc NIPS Workshop on Deep Learning and Unsupervised Feature Learning"},{"key":"ref22","first-page":"1393","article-title":"Efficient FPGA Acceleration of Convolutional Neural Networks Using Logical-3D Compute Array","author":"atul rahman","year":"2016","journal-title":"Design Automation Test in Europe Conference Exhibition (DATE)"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/2744769.2744788"},{"key":"ref42","article-title":"Rapid architectural exploration in designing application-specific processors","author":"wu","year":"2015"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ASPDAC.2016.7428073"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/JRPROC.1952.273898"},{"key":"ref23","first-page":"16","article-title":"Throughput-optimized OpenCL-based FPGA accelerator for large-scale convolutional neural networks","author":"suda","year":"2016","journal-title":"Proc ACM\/SIGDA Int Symp Field-Program Gate Arrays"},{"key":"ref44","first-page":"90","article-title":"A sub-ns response on-chip switched-capacitor DC-DC voltage regulator delivering 3.7W\/mm2 at 90% efficiency using deep-trench capacitors in 32nm SOI CMOS","author":"andersen","year":"2014","journal-title":"IEEE Int Solid-State Circuits Conf (ISSCC) Dig Tech Papers"},{"key":"ref26","first-page":"180","article-title":"A 1.40mm\n$^{2}~141$\nmW 898GOPS sparse neuromorphic processor in 40nm CMOS","author":"knag","year":"2016","journal-title":"Proc IEEE Symp VLSI Circuits"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ISSCC.2015.7063077"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ISSCC.2016.7418007"}],"container-title":["IEEE Journal of Solid-State Circuits"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/4\/7888613\/07801877.pdf?arnumber=7801877","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T16:09:35Z","timestamp":1642003775000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7801877\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,4]]},"references-count":44,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/jssc.2016.2636225","relation":{},"ISSN":["0018-9200","1558-173X"],"issn-type":[{"value":"0018-9200","type":"print"},{"value":"1558-173X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,4]]}}}