{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T09:37:28Z","timestamp":1774690648528,"version":"3.50.1"},"reference-count":34,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018AAA0102700"],"award-info":[{"award-number":["2018AAA0102700"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61874124"],"award-info":[{"award-number":["61874124"]}],"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":["61876173"],"award-info":[{"award-number":["61876173"]}],"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":["61532017"],"award-info":[{"award-number":["61532017"]}],"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":["61772300"],"award-info":[{"award-number":["61772300"]}],"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":["61902375"],"award-info":[{"award-number":["61902375"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["XDC05030201"],"award-info":[{"award-number":["XDC05030201"]}]},{"name":"YESS","award":["YESS2016qnrc001"],"award-info":[{"award-number":["YESS2016qnrc001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Comput."],"published-print":{"date-parts":[[2021,9,1]]},"DOI":"10.1109\/tc.2020.3014632","type":"journal-article","created":{"date-parts":[[2020,8,6]],"date-time":"2020-08-06T20:51:43Z","timestamp":1596747103000},"page":"1511-1525","source":"Crossref","is-referenced-by-count":123,"title":["EnGN: A High-Throughput and Energy-Efficient Accelerator for Large Graph Neural Networks"],"prefix":"10.1109","volume":"70","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8407-2594","authenticated-orcid":false,"given":"Shengwen","family":"Liang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5172-4736","authenticated-orcid":false,"given":"Ying","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5542-7306","authenticated-orcid":false,"given":"Cheng","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3127-3266","authenticated-orcid":false,"given":"Lei","family":"He","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8082-4218","authenticated-orcid":false,"given":"Huawei","family":"Li","sequence":"additional","affiliation":[]},{"given":"Dawen","family":"Xu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0874-814X","authenticated-orcid":false,"given":"Xiaowei","family":"Li","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO.2016.7783759"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001163"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/2541940.2541967"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2017.2761740"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3352460.3358318"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/S1389-1286(00)00083-9"},{"key":"ref11","article-title":"Graph neural networks: A review of methods and applications","author":"zhou","year":"0","journal-title":"CoRR"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref13","first-page":"1263","article-title":"Neural message passing for quantum chemistry","volume":"70","author":"gilmer","year":"0","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref14","first-page":"1025","article-title":"Inductive representation learning on large graphs","author":"hamilton","year":"0","journal-title":"Proc 31st Int Conf Neural Inf Process Syst"},{"key":"ref15","first-page":"933","article-title":"Language modeling with gated convolutional networks","volume":"70","author":"dauphin","year":"0","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref16","article-title":"Recent advances in recurrent neural networks","author":"salehinejad","year":"2018","journal-title":"CoRR"},{"key":"ref17","article-title":"Gated graph sequence neural networks","author":"li","year":"2016","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93417-4_38"},{"key":"ref19","first-page":"375","article-title":"GridGraph: Large-scale graph processing on a single machine using 2-level hierarchical partitioning","author":"zhu","year":"2015","journal-title":"Proc USENIX Annu Tech Conf"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3199523"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/250"},{"key":"ref27","article-title":"GraphRNN: A deep generative model for graphs","author":"you","year":"2018","journal-title":"CoRR"},{"key":"ref3","article-title":"FastGCN: Fast learning with graph convolutional networks via importance sampling","author":"chen","year":"2018","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref6","article-title":"Euler: A distributed graph deep learning framework.","year":"0"},{"key":"ref29","first-page":"669","article-title":"TuX2: Distributed graph computation for machine learning","author":"xiao","year":"2017","journal-title":"Proc 14th USENIX Conf Netw Syst Des Implementation"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3340404"},{"key":"ref8","article-title":"Fast graph representation learning with pytorch geometric","author":"fey","year":"0","journal-title":"Proc Int Conf Learn Representations Workshop Graphs Manifolds"},{"key":"ref7","article-title":"Deep graph library: Towards efficient and scalable deep learning on graphs","author":"wang","year":"0","journal-title":"Proc Int Conf Learn Representations Workshop Graphs Manifolds"},{"key":"ref2","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2017","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref9","first-page":"443","article-title":"Neugraph: Parallel deep neural network computation on large graphs","author":"ma","year":"2019","journal-title":"Proc USENIX Annu Tech Conf"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/PACT.2019.00051"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/LCA.2020.2970395"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/HPCA47549.2020.00012"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972740.43"},{"key":"ref23","article-title":"Bandwidth reduction using importance weighted pruning on ring allreduce","author":"cheng","year":"2019","journal-title":"CoRR"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3123939.3124545"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/LCA.2015.2414456"}],"container-title":["IEEE Transactions on Computers"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/12\/9508207\/09161360.pdf?arnumber=9161360","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T16:05:03Z","timestamp":1642003503000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9161360\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,1]]},"references-count":34,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tc.2020.3014632","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":[[2021,9,1]]}}}