{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T18:10:38Z","timestamp":1785953438748,"version":"3.56.0"},"reference-count":56,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2020,12,4]],"date-time":"2020-12-04T00:00:00Z","timestamp":1607040000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61841404"],"award-info":[{"award-number":["61841404"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Intelligent Systems"],"published-print":{"date-parts":[[2021,5]]},"abstract":"<jats:sec><jats:label\/><jats:p>The advancement of artificial intelligence applications is promoted by developing deep neural networks (DNNs) with increasing sizes and putting forward higher computing power requirements of the processing devices. However, due to the process scaling of complementary metal\u2013oxide\u2013semiconductor technology approaches to the end and the bottleneck of data transmission in the von\u2010Neumann architecture, traditional processing devices are increasingly challenging to meet the requirements of deeper and deeper neural networks. In\u2010memory computing based on nonvolatile memories has emerged as one of the most promising solutions to overcome the bottleneck of data transmission in the von\u2010Neumann architecture. Herein, systematic implementation of the novel flash memory array\u2010based in\u2010memory computing paradigm for DNNs from the device level to the architecture level is presented. The methodology to construct multiplication\u2010and\u2010accumulation units with different structures, hardware implementation schemes of various neural networks, and the discussion of reliability are included. The results show the hardware implementations of the flash memory array\u2010based in\u2010memory computing paradigm for DNN own excellent characteristics such as low\u2010cost, high computing flexibility, and high robustness. With these advantages, in\u2010memory computing paradigms based on flash memory arrays show significant benefits to achieve high scalability and DNNs\u2019 energy efficiency.<\/jats:p><\/jats:sec>","DOI":"10.1002\/aisy.202000161","type":"journal-article","created":{"date-parts":[[2020,12,4]],"date-time":"2020-12-04T10:10:08Z","timestamp":1607076608000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Flash Memory Array for Efficient Implementation of Deep Neural Networks"],"prefix":"10.1002","volume":"3","author":[{"given":"Runze","family":"Han","sequence":"first","affiliation":[{"name":"Institute of Microelectronics Peking University  Beijing 100871 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yachen","family":"Xiang","sequence":"additional","affiliation":[{"name":"Institute of Microelectronics Peking University  Beijing 100871 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Huang","sequence":"additional","affiliation":[{"name":"Institute of Microelectronics Peking University  Beijing 100871 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yihao","family":"Shan","sequence":"additional","affiliation":[{"name":"Institute of Microelectronics Peking University  Beijing 100871 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyan","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Microelectronics Peking University  Beijing 100871 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6286-0423","authenticated-orcid":false,"given":"Jinfeng","family":"Kang","sequence":"additional","affiliation":[{"name":"Institute of Microelectronics Peking University  Beijing 100871 China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2020,12,4]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2017.2761740"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41928-018-0059-3"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2017.3641648"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.3390\/bdcc2030026"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/530144a"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/85.238389"},{"key":"e_1_2_8_8_1","unstructured":"J.Jeddeloh B.Keeth inVLSI Symp. IEEE Piscataway NJ2012 p.87."},{"key":"e_1_2_8_9_1","unstructured":"D. U.Lee K. W.Kim K. W.Kim H.Kim J. Y.Kim Y. J.Park J. H.Kim D. S.Kim H. B.Park J. W.Shin J. H.Cho K. H.Kwon M. J.Kim J.Lee K. W.Park B.Chung S.Hong inIEEE ISSCC Technical Digest IEEE San Francisco CA2014 p.432."},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2011.2179749"},{"key":"e_1_2_8_11_1","first-page":"11","volume":"59","author":"Chen Y.","year":"2016","journal-title":"Commun. ACM"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001159"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2016.2616357"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001140"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001139"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41928-018-0092-2"},{"key":"e_1_2_8_17_1","first-page":"12","volume":"25","author":"Yu S.","year":"2013","journal-title":"Adv. Mater."},{"key":"e_1_2_8_18_1","first-page":"9","volume":"30","author":"Hu M.","year":"2018","journal-title":"Adv. Mater."},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14441"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1002\/adfm.201202383"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1254642"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1038\/srep31510"},{"key":"e_1_2_8_23_1","doi-asserted-by":"publisher","DOI":"10.1038\/nmat3415"},{"key":"e_1_2_8_24_1","first-page":"9","volume":"2","author":"Jeong D. S.","year":"2016","journal-title":"Adv. Electron. Mater."},{"key":"e_1_2_8_25_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41563-018-0260-9"},{"key":"e_1_2_8_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1369-7021(11)70302-9"},{"key":"e_1_2_8_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSSC.2016.2622960"},{"key":"e_1_2_8_28_1","unstructured":"X.Guo F. M.Bayat M.Bavandpour M.Klachko M. R.Mahmoodi M.Prezioso K. K.Likharev D. B.Strukov inIEDM Technical Digest IEEE San Francisco CA2017 p.151."},{"key":"e_1_2_8_29_1","unstructured":"Y. Y.Lin F. M.Lee M. H.Lee W. C.Chen H. L.Lung K. C.Wang C. Y.Lu inIEDM Technical Digest 2018 IEEE San Francisco CAp.39."},{"key":"e_1_2_8_30_1","doi-asserted-by":"publisher","DOI":"10.1002\/admt.201800720"},{"key":"e_1_2_8_31_1","unstructured":"Y.Xiang P.Huang Z.Zhou R.Han Y.Jiang Q.Shu Z.Su Y.Liu X.Liu J.Kang inIEEE ISCAS IEEE Sapporo Japan2019."},{"key":"e_1_2_8_32_1","unstructured":"Y.Xiang P.Huang H.Yang K.Wang R.Han W.Shen Y.Feng C.Liu X.Liu J.Kang inIEDM Tech. Dig.2019 p.919."},{"key":"e_1_2_8_33_1","first-page":"52","volume":"5","author":"Agarwal S.","year":"2019","journal-title":"IEEE J. Explor. Solid-State Computat."},{"key":"e_1_2_8_34_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41928-019-0331-1"},{"key":"e_1_2_8_35_1","unstructured":"M.Kim M.Liu L.Everson G.Park Y.Jeon S.Kim S.Lee S.Song C. H.Kim inIEDM Technical Digest2019 IEEE San Francisco CAp.923."},{"key":"e_1_2_8_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TED.2017.2775233"},{"key":"e_1_2_8_37_1","unstructured":"G.Malavena A. S.Spinelli C. M.Compagnoni inIEDM Technical Digest 2018 IEEE San Francisco CAp.35."},{"key":"e_1_2_8_38_1","first-page":"11","volume":"66","author":"Malavena G.","year":"2019","journal-title":"IEEE Trans. Electron Devices"},{"key":"e_1_2_8_39_1","first-page":"43","volume":"30","author":"Oh S.","year":"2019","journal-title":"Nanotechnology"},{"key":"e_1_2_8_40_1","doi-asserted-by":"publisher","DOI":"10.1088\/2053-1583\/ab23ba"},{"key":"e_1_2_8_41_1","unstructured":"H. T.Lue P. K.Hsu M. L.Wei T. H.Yeh P. Y.Du W. C.Chen K. C.Wang C. Y.Lu inIEDM Technical Digest 2019 IEEE San Francisco CAp.915."},{"key":"e_1_2_8_42_1","first-page":"5","volume":"66","author":"Han R.","year":"2019","journal-title":"IEEE Trans. Circuits Syst. I"},{"key":"e_1_2_8_43_1","unstructured":"P.Huang Y.Xiang Y.Zhao C.Liu B.Gao H.Wu H.Qian X.Liu J.Kang inIEDM Technical Digest 2018 p.937."},{"key":"e_1_2_8_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/2856125"},{"key":"e_1_2_8_45_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"e_1_2_8_46_1","doi-asserted-by":"crossref","unstructured":"T.Tang L.Xia P.Gu Y.Wang H.Yang inASP-DAC Digest2017 IEEE Chibap.782.","DOI":"10.1109\/ASPDAC.2017.7858419"},{"key":"e_1_2_8_47_1","unstructured":"B.Li L.Xia P.Gu Y.Wang H.Yang inDAC Digest2015 ACM San Francisco CAp.13."},{"key":"e_1_2_8_48_1","unstructured":"P. Y.Chen X.Peng S.Yu inIEDM Technical Digest2017 IEEE San Francisco CAp.135."},{"key":"e_1_2_8_49_1","first-page":"1","volume":"13","author":"Li B.","year":"2015","journal-title":"Proc. DAC"},{"key":"e_1_2_8_50_1","first-page":"26","volume":"5","author":"Barranco B. L.","year":"2011","journal-title":"Front. Neurosci."},{"key":"e_1_2_8_51_1","doi-asserted-by":"crossref","unstructured":"P. U.Diehl D.Neil J.Binas M.Cook S.-C.Liu M.Pfeiffer inProc. Int. Joint Conf. Neural Netw. (IJCNN) IEEE Killarney Ireland2015 p.1.","DOI":"10.1109\/IJCNN.2015.7280696"},{"key":"e_1_2_8_52_1","doi-asserted-by":"publisher","DOI":"10.1109\/TED.2020.2987439"},{"key":"e_1_2_8_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2003.811702"},{"key":"e_1_2_8_54_1","unstructured":"H.Zhang Y. N.Dauphin T.Ma arXiv2019 1901.09321."},{"key":"e_1_2_8_55_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11390-016-1608-8"},{"key":"e_1_2_8_56_1","doi-asserted-by":"crossref","unstructured":"J.Woo X.Peng S.Yu inISCAS2018 IEEE Florencep.1.","DOI":"10.1109\/ISCAS.2018.8351735"},{"key":"e_1_2_8_57_1","doi-asserted-by":"publisher","DOI":"10.1109\/TED.2020.3037585"}],"container-title":["Advanced Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/aisy.202000161","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/aisy.202000161","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/aisy.202000161","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T19:42:37Z","timestamp":1759866157000},"score":1,"resource":{"primary":{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/10.1002\/aisy.202000161"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,4]]},"references-count":56,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2021,5]]}},"alternative-id":["10.1002\/aisy.202000161"],"URL":"https:\/\/doi.org\/10.1002\/aisy.202000161","archive":["Portico"],"relation":{},"ISSN":["2640-4567","2640-4567"],"issn-type":[{"value":"2640-4567","type":"print"},{"value":"2640-4567","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12,4]]},"assertion":[{"value":"2020-07-15","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-12-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"2000161"}}