{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T16:09:53Z","timestamp":1781885393978,"version":"3.54.5"},"reference-count":40,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,12,5]],"date-time":"2021-12-05T00:00:00Z","timestamp":1638662400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,5]],"date-time":"2021-12-05T00:00:00Z","timestamp":1638662400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,5]],"date-time":"2021-12-05T00:00:00Z","timestamp":1638662400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,5]]},"DOI":"10.1109\/dac18074.2021.9586239","type":"proceedings-article","created":{"date-parts":[[2021,11,8]],"date-time":"2021-11-08T23:30:34Z","timestamp":1636414234000},"page":"919-924","source":"Crossref","is-referenced-by-count":19,"title":["EMGraph: Fast Learning-Based Electromigration Analysis for Multi-Segment Interconnect Using Graph Convolution Networks"],"prefix":"10.1109","author":[{"given":"Wentian","family":"Jin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheriff","family":"Sadiqbatcha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaoyi","family":"Peng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheldon X.-D.","family":"Tan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","article-title":"Electomigration in ULSI Interconnects, ser","author":"tan","year":"2010","journal-title":"International Series on Advances in Solid State Electronics and Technology Word Scientific"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/DAC18072.2020.9218643"},{"key":"ref33","author":"goodfellow","year":"2016","journal-title":"Deep Learning"},{"key":"ref32","first-page":"296","article-title":"Emgan: Data-driven fast stress analysis for multi-segment interconnects","author":"jin","year":"2020","journal-title":"Proc IEEE Int Conf on Computer Design (ICCD)"},{"key":"ref31","first-page":"1","article-title":"A customized graph neural network model for guiding analog ic placement","author":"li","year":"2020","journal-title":"2020 IEEE\/ACM International Conference on Computer-Aided Design (ICCAD)"},{"key":"ref30","first-page":"1","article-title":"Gcn-rl circuit designer: Transferable transistor sizing with graph neural networks and reinforcement learning","author":"wang","year":"2020","journal-title":"2020 57th ACM\/IEEE Design Automation Conference (DAC)"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2019.109020"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2018.08.029"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2018.10.045"},{"key":"ref34","first-page":"arxiv:1711.10561","article-title":"Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations","author":"raissi","year":"2017","journal-title":"ArXiv e-prints"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/2897937.2898070"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TDMR.2017.2746660"},{"key":"ref40","article-title":"Deep graph library: A graph-centric, highly-performant package for graph neural networks","author":"wang","year":"2019","journal-title":"ICLR Workshop on Representation Learning on Graphs and Manifolds"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2017.2666723"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TVLSI.2018.2800707"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAD.2017.8203861"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TVLSI.2018.2861358"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3195970.3196099"},{"key":"ref17","first-page":"1","article-title":"Fast analytic electromigration analysis for general multisegment interconnect wires","author":"chen","year":"2019","journal-title":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems"},{"key":"ref18","article-title":"VLSI Systems Long-Term Reliability – Modeling","author":"tan","year":"2019","journal-title":"Simulation and Optimization"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1063\/1.354073"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/IRPS.2013.6531951"},{"key":"ref28","first-page":"1","article-title":"Paragraph: Layout parasitics and device parameter prediction using graph neural networks","author":"ren","year":"2020","journal-title":"2020 57th ACM\/IEEE Design Automation Conference (DAC)"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1063\/1.322842"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.23919\/DATE48585.2020.9116513"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.microrel.2010.01.007"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.mee.2013.08.013"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/DAC18072.2020.9218582"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TDMR.2015.2508447"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2016.2524540"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/T-ED.1969.16754"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2016.2523898"},{"key":"ref1","year":"2015","journal-title":"International Technology Roadmap for Semiconductors (ITRS)"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TVLSI.2018.2800707"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAD.2017.8203775"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TDMR.2018.2874244"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"lecun","year":"2015","journal-title":"Nature"},{"key":"ref26","first-page":"1024","article-title":"Inductive representation learning on large graphs","volume":"30","author":"hamilton","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref25","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2017","journal-title":"International Conference on Learning Representations"}],"event":{"name":"2021 58th ACM\/IEEE Design Automation Conference (DAC)","location":"San Francisco, CA, USA","start":{"date-parts":[[2021,12,5]]},"end":{"date-parts":[[2021,12,9]]}},"container-title":["2021 58th ACM\/IEEE Design Automation Conference (DAC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9585997\/9586083\/09586239.pdf?arnumber=9586239","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T16:55:54Z","timestamp":1652201754000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9586239\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,5]]},"references-count":40,"URL":"https:\/\/doi.org\/10.1109\/dac18074.2021.9586239","relation":{},"subject":[],"published":{"date-parts":[[2021,12,5]]}}}