{"id":"https://openalex.org/W4410583520","doi":"https://doi.org/10.23919/date64628.2025.10992959","title":"IR-Fusion: A Fusion Framework for Static IR Drop Analysis Combining Numerical Solution and Machine Learning","display_name":"IR-Fusion: A Fusion Framework for Static IR Drop Analysis Combining Numerical Solution and Machine Learning","publication_year":2025,"publication_date":"2025-03-31","ids":{"openalex":"https://openalex.org/W4410583520","doi":"https://doi.org/10.23919/date64628.2025.10992959"},"language":"en","primary_location":{"id":"doi:10.23919/date64628.2025.10992959","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date64628.2025.10992959","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Design, Automation & Test in Europe Conference (DATE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101544239","display_name":"Feng Guo","orcid":"https://orcid.org/0009-0000-5165-5515"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Feng Guo","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016813457","display_name":"Jianwang Zhai","orcid":"https://orcid.org/0000-0002-1581-3536"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianwang Zhai","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029730419","display_name":"Jingyu Jia","orcid":"https://orcid.org/0009-0001-6027-4842"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyu Jia","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100320744","display_name":"Jiawei Liu","orcid":"https://orcid.org/0000-0002-2774-1509"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawei Liu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035246366","display_name":"Kang Zhao","orcid":"https://orcid.org/0000-0002-8321-2804"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kang Zhao","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051340429","display_name":"Bei Yu","orcid":"https://orcid.org/0000-0001-6406-4810"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bei Yu","raw_affiliation_strings":["The Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100705849","display_name":"Chuan Shi","orcid":"https://orcid.org/0000-0002-3734-0266"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuan Shi","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101544239"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14184417,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12304","display_name":"Radiative Heat Transfer Studies","score":0.663100004196167,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12304","display_name":"Radiative Heat Transfer Studies","score":0.663100004196167,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.8043323755264282},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5503199100494385},{"id":"https://openalex.org/keywords/drop","display_name":"Drop (telecommunication)","score":0.5011365413665771},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.47541528940200806},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36694857478141785},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.05387115478515625}],"concepts":[{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.8043323755264282},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5503199100494385},{"id":"https://openalex.org/C2781345722","wikidata":"https://www.wikidata.org/wiki/Q5308388","display_name":"Drop (telecommunication)","level":2,"score":0.5011365413665771},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.47541528940200806},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36694857478141785},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.05387115478515625},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/date64628.2025.10992959","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date64628.2025.10992959","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Design, Automation & Test in Europe Conference (DATE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1076360168","display_name":null,"funder_award_id":"2022YFB2901100","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G1378428181","display_name":null,"funder_award_id":"4244107,QY24216,QY24204","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G2406629704","display_name":null,"funder_award_id":"U20B2045,U1936220,62192784,62172052,62002029,61772082,62404021","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1902237438","https://openalex.org/W1924762813","https://openalex.org/W2014505173","https://openalex.org/W2030651811","https://openalex.org/W2089024363","https://openalex.org/W2096178444","https://openalex.org/W2099647435","https://openalex.org/W2118076222","https://openalex.org/W2131254145","https://openalex.org/W2167232953","https://openalex.org/W2183341477","https://openalex.org/W2296073425","https://openalex.org/W3142849873","https://openalex.org/W3144470797","https://openalex.org/W3148263180","https://openalex.org/W3186706634","https://openalex.org/W4200338900","https://openalex.org/W4253785077","https://openalex.org/W4289752563","https://openalex.org/W4310904528","https://openalex.org/W4313340689","https://openalex.org/W4385245566","https://openalex.org/W4399487303","https://openalex.org/W4401568772","https://openalex.org/W4404133602","https://openalex.org/W4404134074","https://openalex.org/W6783115343"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2152662039"],"abstract_inverted_index":{"IR":[0,42,97],"Drop":[1],"analysis":[2,40],"for":[3],"on-chip":[4],"power":[5],"grids":[6],"(PGs)":[7],"is":[8,104,127,153,161,188,201],"vital":[9],"but":[10,34],"computationally":[11],"challenging":[12],"due":[13],"to":[14,52,79,85,106,115,129,163,190,215],"the":[15,19,54,60,87,101,137,140,147,151,176,191,217],"rapid":[16,39],"growth":[17],"in":[18,95],"integrated":[20],"circuit":[21],"(IC)":[22],"scale.":[23],"Traditional":[24],"numerical":[25,57,81,102,124,132,138,222],"methods":[26,48,82,207],"employed":[27],"by":[28],"current":[29],"EDA":[30],"software":[31],"are":[32,113],"accurate":[33],"extremely":[35],"time-consuming.":[36],"To":[37,173],"achieve":[38,86,216],"of":[41,56,62,142,150,168,180,195],"drop,":[43],"various":[44],"machine":[45],"learning":[46,186],"(ML)":[47],"have":[49],"been":[50,67],"introduced":[51],"address":[53],"inefficiency":[55],"methods.":[58,223],"However,":[59],"issue":[61],"interpretability":[63],"or":[64],"scalability":[65],"has":[66],"limiting":[68],"practical":[69],"applications.":[70],"In":[71,119],"this":[72],"work,":[73],"we":[74],"propose":[75],"IR-Fusion,":[76],"which":[77],"aims":[78],"combine":[80],"with":[83,175,221],"ML":[84,111],"trade-off":[88],"and":[89,93,110,155,166,178],"complementarity":[90],"between":[91],"accuracy":[92,117,200,219],"efficiency":[94],"static":[96],"drop":[98],"analysis.":[99],"Specifically,":[100],"method":[103],"used":[105],"obtain":[107],"rough":[108,131],"solutions":[109],"models":[112],"utilized":[114],"improve":[116],"further.":[118],"our":[120],"framework,":[121],"an":[122,156,183],"efficient":[123],"solver,":[125],"AMG-PCG,":[126],"applied":[128,189],"get":[130],"solutions.":[133],"Then,":[134],"based":[135],"on":[136,213],"solution,":[139],"fusion":[141],"hierarchical":[143],"numerical-structural":[144],"information":[145],"representing":[146],"multilayer":[148],"structure":[149],"PG":[152,181],"employed,":[154],"Inception":[157],"Attention":[158],"U-Net":[159],"model":[160],"designed":[162],"capture":[164],"details":[165],"interaction":[167],"features":[169],"at":[170],"different":[171],"scales.":[172],"cope":[174],"limitations":[177],"diversity":[179],"designs,":[182],"augmented":[184],"curriculum":[185],"strategy":[187],"training":[192],"phase.":[193],"Evaluation":[194],"IR-Fusion":[196],"shows":[197],"that":[198],"its":[199],"significantly":[202],"better":[203],"than":[204],"previous":[205],"ML-based":[206],"while":[208],"requiring":[209],"considerably":[210],"less":[211],"iteration":[212],"solver":[214],"same":[218],"compared":[220]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}