{"id":"https://openalex.org/W3175617909","doi":"https://doi.org/10.1145/3453688.3461526","title":"PALBBD","display_name":"PALBBD","publication_year":2021,"publication_date":"2021-06-18","ids":{"openalex":"https://openalex.org/W3175617909","doi":"https://doi.org/10.1145/3453688.3461526","mag":"3175617909"},"language":"en","primary_location":{"id":"doi:10.1145/3453688.3461526","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3453688.3461526","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 Great Lakes Symposium on VLSI","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/A5057257864","display_name":"Zhou Jin","orcid":"https://orcid.org/0000-0002-0632-9494"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhou Jin","raw_affiliation_strings":["China University of Petroleum-Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100745500","display_name":"Feng Tian","orcid":"https://orcid.org/0000-0001-5180-6002"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tian Feng","raw_affiliation_strings":["China University of Petroleum-Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112733268","display_name":"Yiru Duan","orcid":null},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiru Duan","raw_affiliation_strings":["China University of Petroleum-Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111726884","display_name":"Xiao Wu","orcid":"https://orcid.org/0009-0004-7013-6234"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao Wu","raw_affiliation_strings":["Huada Empyrean Software Co. Ltd, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huada Empyrean Software Co. Ltd, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034379481","display_name":"Minghou Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Minghou Cheng","raw_affiliation_strings":["Huada Empyrean Software Co. Ltd, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huada Empyrean Software Co. Ltd, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069323283","display_name":"Zhenya Zhou","orcid":"https://orcid.org/0000-0002-2645-6386"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhenya Zhou","raw_affiliation_strings":["Huada Empyrean Software Co. Ltd, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huada Empyrean Software Co. Ltd, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100444152","display_name":"Weifeng Liu","orcid":"https://orcid.org/0000-0002-2150-5759"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weifeng Liu","raw_affiliation_strings":["China University of Petroleum-Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5057257864"],"corresponding_institution_ids":["https://openalex.org/I204553293"],"apc_list":null,"apc_paid":null,"fwci":0.5085,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.63967888,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"327","last_page":"332"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9993000030517578,"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/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9993000030517578,"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":0.9986000061035156,"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/T11697","display_name":"Numerical Methods and Algorithms","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/jacobian-matrix-and-determinant","display_name":"Jacobian matrix and determinant","score":0.8683490753173828},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.7832930088043213},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6905322074890137},{"id":"https://openalex.org/keywords/diagonal","display_name":"Diagonal","score":0.619396448135376},{"id":"https://openalex.org/keywords/schur-complement","display_name":"Schur complement","score":0.5445852279663086},{"id":"https://openalex.org/keywords/block-matrix","display_name":"Block matrix","score":0.5397565960884094},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.49722054600715637},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.4901219308376312},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4843667447566986},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4785912036895752},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.46525245904922485},{"id":"https://openalex.org/keywords/newtons-method","display_name":"Newton's method","score":0.4301464259624481},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.42552292346954346},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35322949290275574},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.29148542881011963},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22681975364685059}],"concepts":[{"id":"https://openalex.org/C200331156","wikidata":"https://www.wikidata.org/wiki/Q506041","display_name":"Jacobian matrix and determinant","level":2,"score":0.8683490753173828},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.7832930088043213},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6905322074890137},{"id":"https://openalex.org/C130367717","wikidata":"https://www.wikidata.org/wiki/Q189791","display_name":"Diagonal","level":2,"score":0.619396448135376},{"id":"https://openalex.org/C2731191","wikidata":"https://www.wikidata.org/wiki/Q1778169","display_name":"Schur complement","level":3,"score":0.5445852279663086},{"id":"https://openalex.org/C85817219","wikidata":"https://www.wikidata.org/wiki/Q884772","display_name":"Block matrix","level":3,"score":0.5397565960884094},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.49722054600715637},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.4901219308376312},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4843667447566986},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4785912036895752},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.46525245904922485},{"id":"https://openalex.org/C85189116","wikidata":"https://www.wikidata.org/wiki/Q374195","display_name":"Newton's method","level":3,"score":0.4301464259624481},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.42552292346954346},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35322949290275574},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.29148542881011963},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22681975364685059},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3453688.3461526","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3453688.3461526","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 Great Lakes Symposium on VLSI","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2102138118","display_name":null,"funder_award_id":"2462020YXZZ024","funder_id":"https://openalex.org/F4320326291","funder_display_name":"Science Foundation of China University of Petroleum, Beijing"},{"id":"https://openalex.org/G3472349540","display_name":"\u9ad8\u53ef\u6269\u5c55\u3001\u9ad8\u6027\u80fd\u548c\u9ad8\u5b9e\u7528\u7684\u7a00\u758f\u77e9\u9635\u8ba1\u7b97\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61972415","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/F4320326291","display_name":"Science Foundation of China University of Petroleum, Beijing","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1645555890","https://openalex.org/W1964130846","https://openalex.org/W1976872979","https://openalex.org/W1977937833","https://openalex.org/W1991452943","https://openalex.org/W1996309908","https://openalex.org/W2019190420","https://openalex.org/W2038618128","https://openalex.org/W2060067233","https://openalex.org/W2098234232","https://openalex.org/W2125019445","https://openalex.org/W2133545895","https://openalex.org/W2156967549","https://openalex.org/W2577920159","https://openalex.org/W2909744688","https://openalex.org/W3212893044"],"related_works":["https://openalex.org/W3040723915","https://openalex.org/W1901133132","https://openalex.org/W1896162644","https://openalex.org/W2127159799","https://openalex.org/W4287724094","https://openalex.org/W2068966571","https://openalex.org/W2188650732","https://openalex.org/W1614135785","https://openalex.org/W2385824356","https://openalex.org/W2532207692"],"abstract_inverted_index":{"With":[0],"the":[1,14,58,63,73,80,88,96,103,110,116,122,131,136,147,158],"increasing":[2],"complexity":[3],"of":[4,62,98,105,112],"integrated":[5,145],"circuits,":[6],"it":[7],"is":[8,142],"becoming":[9],"cumulatively":[10],"challenging":[11],"to":[12,43,86,108,120,129,146,165],"solve":[13,44],"entire":[15],"large-scale":[16],"nonlinear":[17],"algebraic":[18],"system":[19],"in":[20,53,67],"DC":[21,45],"analysis":[22],"within":[23],"reasonable":[24],"simulation":[25],"time":[26],"and":[27,50,101,144,150,168],"without":[28],"accuracy":[29,52],"lost.":[30],"For":[31],"this":[32,54],"reason,":[33],"we":[34,78,94,124],"present":[35],"an":[36,68],"efficient":[37],"parallel":[38,91],"arclength":[39,161],"approach":[40],"called":[41],"PALBBD":[42,141],"problems":[46],"for":[47,90,135],"large":[48],"capacity":[49],"full":[51],"paper.":[55],"We":[56],"process":[57],"m+1":[59],"dimensions":[60],"equation":[61,128],"Newton-Raphson":[64],"(NR)":[65],"iteration":[66],"alternative":[69],"way,":[70],"which":[71],"maintains":[72],"Jacobian":[74],"matrix":[75,89],"structure.":[76],"Besides,":[77],"exploit":[79],"bordered":[81],"block":[82],"diagonal":[83],"(BBD)":[84],"form":[85],"save":[87],"computing.":[92],"Moreover,":[93],"check":[95],"convergence":[97],"each":[99],"sub-partition":[100],"bypass":[102,170],"calculations":[104],"converged":[106],"ones":[107],"reduce":[109],"amount":[111],"unnecessary":[113],"computations":[114],"during":[115],"iteration.":[117],"In":[118],"order":[119],"ensure":[121],"accuracy,":[123],"use":[125],"a":[126],"correction":[127],"replace":[130],"Schur":[132],"complement":[133],"updating":[134],"bypassed":[137],"sub-partitions.":[138],"The":[139],"proposed":[140],"implemented":[143],"SPICE":[148],"simulator":[149],"verified":[151],"by":[152],"72":[153],"real-world":[154],"circuits.":[155],"It":[156],"outperforms":[157],"conventional":[159],"serial":[160],"method":[162],"with":[163],"up":[164],"73.93X":[166],"speedup":[167],"45%":[169],"ratio.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2026-06-06T09:05:17.133730","created_date":"2021-07-05T00:00:00"}
