{"id":"https://openalex.org/W4415003383","doi":"https://doi.org/10.1109/mlcad65511.2025.11189189","title":"Fast Chip Transient Temperature Simulation via Machine Learning","display_name":"Fast Chip Transient Temperature Simulation via Machine Learning","publication_year":2025,"publication_date":"2025-09-08","ids":{"openalex":"https://openalex.org/W4415003383","doi":"https://doi.org/10.1109/mlcad65511.2025.11189189"},"language":"en","primary_location":{"id":"doi:10.1109/mlcad65511.2025.11189189","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlcad65511.2025.11189189","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 ACM/IEEE 7th Symposium on Machine Learning for CAD (MLCAD)","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/A5114881012","display_name":"Mohammadamin Hajikhodaverdian","orcid":null},"institutions":[{"id":"https://openalex.org/I33434090","display_name":"University of Massachusetts Boston","ror":"https://ror.org/04ydmy275","country_code":"US","type":"education","lineage":["https://openalex.org/I33434090"]},{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mohammadamin Hajikhodaverdian","raw_affiliation_strings":["Boston University,Dept. of Electrical &amp; Computer Engineering,Boston,MA,USA"],"affiliations":[{"raw_affiliation_string":"Boston University,Dept. of Electrical &amp; Computer Engineering,Boston,MA,USA","institution_ids":["https://openalex.org/I111088046","https://openalex.org/I33434090"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015719218","display_name":"Sherief Reda","orcid":"https://orcid.org/0000-0001-8232-4516"},"institutions":[{"id":"https://openalex.org/I27804330","display_name":"Brown University","ror":"https://ror.org/05gq02987","country_code":"US","type":"education","lineage":["https://openalex.org/I27804330"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sherief Reda","raw_affiliation_strings":["Brown University,School of Engineering,Providence,RI,USA"],"affiliations":[{"raw_affiliation_string":"Brown University,School of Engineering,Providence,RI,USA","institution_ids":["https://openalex.org/I27804330"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064676631","display_name":"Ayse K. Coskun","orcid":"https://orcid.org/0000-0002-6554-088X"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]},{"id":"https://openalex.org/I33434090","display_name":"University of Massachusetts Boston","ror":"https://ror.org/04ydmy275","country_code":"US","type":"education","lineage":["https://openalex.org/I33434090"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ayse K. Coskun","raw_affiliation_strings":["Boston University,Dept. of Electrical &amp; Computer Engineering,Boston,MA,USA"],"affiliations":[{"raw_affiliation_string":"Boston University,Dept. of Electrical &amp; Computer Engineering,Boston,MA,USA","institution_ids":["https://openalex.org/I111088046","https://openalex.org/I33434090"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5114881012"],"corresponding_institution_ids":["https://openalex.org/I111088046","https://openalex.org/I33434090"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.299398,"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":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10558","display_name":"Advancements in Semiconductor Devices and Circuit Design","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T10558","display_name":"Advancements in Semiconductor Devices and Circuit Design","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10363","display_name":"Low-power high-performance VLSI design","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/transient","display_name":"Transient (computer programming)","score":0.7516999840736389},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.6079000234603882},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.5767999887466431},{"id":"https://openalex.org/keywords/thermal","display_name":"Thermal","score":0.4205999970436096},{"id":"https://openalex.org/keywords/chip","display_name":"Chip","score":0.4185999929904938},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.3752000033855438},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.3601999878883362},{"id":"https://openalex.org/keywords/transistor","display_name":"Transistor","score":0.35920000076293945},{"id":"https://openalex.org/keywords/transient-response","display_name":"Transient response","score":0.35600000619888306}],"concepts":[{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.7516999840736389},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6446999907493591},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6079000234603882},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.5767999887466431},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44699999690055847},{"id":"https://openalex.org/C204530211","wikidata":"https://www.wikidata.org/wiki/Q752823","display_name":"Thermal","level":2,"score":0.4205999970436096},{"id":"https://openalex.org/C165005293","wikidata":"https://www.wikidata.org/wiki/Q1074500","display_name":"Chip","level":2,"score":0.4185999929904938},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3840999901294708},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3752000033855438},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.3601999878883362},{"id":"https://openalex.org/C172385210","wikidata":"https://www.wikidata.org/wiki/Q5339","display_name":"Transistor","level":3,"score":0.35920000076293945},{"id":"https://openalex.org/C85761212","wikidata":"https://www.wikidata.org/wiki/Q1974593","display_name":"Transient response","level":2,"score":0.35600000619888306},{"id":"https://openalex.org/C530198007","wikidata":"https://www.wikidata.org/wiki/Q80831","display_name":"Integrated circuit","level":2,"score":0.33629998564720154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33500000834465027},{"id":"https://openalex.org/C72293138","wikidata":"https://www.wikidata.org/wiki/Q909741","display_name":"Temperature measurement","level":2,"score":0.33329999446868896},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.33009999990463257},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.31690001487731934},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.31540000438690186},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.3057999908924103},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.28940001130104065},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.28349998593330383},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C168068576","wikidata":"https://www.wikidata.org/wiki/Q190241","display_name":"Thermocouple","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C8171440","wikidata":"https://www.wikidata.org/wiki/Q903414","display_name":"Steady state (chemistry)","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C134146338","wikidata":"https://www.wikidata.org/wiki/Q1815901","display_name":"Electronic circuit","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C2989121073","wikidata":"https://www.wikidata.org/wiki/Q1309019","display_name":"Transient analysis","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlcad65511.2025.11189189","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlcad65511.2025.11189189","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 ACM/IEEE 7th Symposium on Machine Learning for CAD (MLCAD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1591018827","https://openalex.org/W2034062945","https://openalex.org/W2035224686","https://openalex.org/W2060285933","https://openalex.org/W2112121929","https://openalex.org/W2123861683","https://openalex.org/W2129960401","https://openalex.org/W2149472303","https://openalex.org/W2162404471","https://openalex.org/W2170382128","https://openalex.org/W2942961753","https://openalex.org/W2961373026","https://openalex.org/W3043514336","https://openalex.org/W3127939301","https://openalex.org/W3128700355","https://openalex.org/W3163019281","https://openalex.org/W3167204903","https://openalex.org/W4213229848","https://openalex.org/W4229451260","https://openalex.org/W4297822234","https://openalex.org/W4386763791","https://openalex.org/W4389162439","https://openalex.org/W4409282681","https://openalex.org/W4410552988"],"related_works":[],"abstract_inverted_index":{"With":[0],"growing":[1],"transistor":[2],"densities,":[3],"analyzing":[4],"temperature":[5,41,144],"in":[6,162],"2D":[7],"and":[8,17,55,83,97,122,182,187],"3D":[9],"integrated":[10],"circuits":[11],"(ICs)":[12],"is":[13],"becoming":[14],"more":[15,179],"complicated":[16],"critical.":[18],"Finite-element":[19],"solvers":[20,60],"give":[21],"accurate":[22],"results,":[23],"but":[24],"a":[25,46,81,156,164,191,194],"single":[26],"transient":[27,123,188],"run":[28],"can":[29,177],"take":[30,63],"hours":[31,64,98],"or":[32],"even":[33],"days.":[34],"Compact":[35],"thermal":[36,54,124],"models":[37,79,92],"(CTMs)":[38],"shorten":[39],"the":[40,51,107,142,200],"simulation":[42,189],"running":[43],"time":[44],"using":[45,75],"numerical":[47,71],"solver":[48],"based":[49],"on":[50],"duality":[52],"between":[53],"electric":[56],"properties.":[57],"However,":[58,89],"CTM":[59,169],"often":[61],"still":[62],"for":[65,86,155,185],"small-scale":[66],"chips":[67],"because":[68],"of":[69,99,159,190],"iterative":[70],"solvers.":[72],"Recent":[73],"work":[74],"machine":[76],"learning":[77],"(ML)":[78],"creates":[80],"fast":[82],"reliable":[84],"framework":[85,114,131,176],"predicting":[87],"temperature.":[88],"current":[90],"ML":[91,113],"demand":[93],"large":[94,127],"input":[95],"samples":[96],"GPU":[100],"training":[101,154],"to":[102,119,140],"reach":[103],"acceptable":[104],"accuracy.To":[105],"overcome":[106],"challenges":[108],"stated,":[109],"we":[110],"design":[111],"an":[112],"that":[115,174],"couples":[116],"with":[117,136,166,193],"CTMs":[118],"accelerate":[120],"steady-state":[121,186],"analysis":[125,134],"without":[126],"data":[128],"inputs.":[129],"Our":[130],"combines":[132],"principal-component":[133],"(PCA)":[135],"closed-form":[137],"linear":[138,147],"regression":[139,148],"predict":[141],"on-chip":[143],"directly.":[145],"The":[146],"weights":[149],"are":[150],"solved":[151],"analytically,":[152],"so":[153],"grid":[157],"size":[158],"512\u00d7512":[160],"finishes":[161],"under":[163],"minute":[165],"only":[167],"15\u201320":[168],"samples.":[170],"Experimental":[171],"results":[172],"show":[173],"our":[175],"achieve":[178],"than":[180],"33\u00d7":[181],"49.6\u00d7":[183],"speedup":[184],"chip":[192],"245.95mm<sup":[195],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[196,206],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[197],"footprint,":[198],"keeping":[199],"mean":[201],"squared":[202],"error":[203],"below":[204],"0.1\u00b0C<sup":[205],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>.":[207]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
