{"id":"https://openalex.org/W4390098039","doi":"https://doi.org/10.1109/iccd58817.2023.00057","title":"Delay-Driven Physically-Aware Logic Synthesis with Informed Search","display_name":"Delay-Driven Physically-Aware Logic Synthesis with Informed Search","publication_year":2023,"publication_date":"2023-11-06","ids":{"openalex":"https://openalex.org/W4390098039","doi":"https://doi.org/10.1109/iccd58817.2023.00057"},"language":"en","primary_location":{"id":"doi:10.1109/iccd58817.2023.00057","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccd58817.2023.00057","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 41st International Conference on Computer Design (ICCD)","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/A5016164327","display_name":"Linyu Zhu","orcid":"https://orcid.org/0000-0003-1822-3221"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Linyu Zhu","raw_affiliation_strings":["University of Michigan &#x2013; Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"University of Michigan &#x2013; Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061878430","display_name":"Xinfei Guo","orcid":"https://orcid.org/0000-0002-2374-3953"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinfei Guo","raw_affiliation_strings":["University of Michigan &#x2013; Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"University of Michigan &#x2013; Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5016164327"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":1.1933,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.79389957,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"327","last_page":"335"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9988999962806702,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7493664026260376},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6313657164573669},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.5443453788757324},{"id":"https://openalex.org/keywords/logic-synthesis","display_name":"Logic synthesis","score":0.4805920124053955},{"id":"https://openalex.org/keywords/logic-gate","display_name":"Logic gate","score":0.43362003564834595},{"id":"https://openalex.org/keywords/network-routing","display_name":"Network routing","score":0.41228634119033813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2318142056465149},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20668020844459534},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.17376208305358887}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7493664026260376},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6313657164573669},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.5443453788757324},{"id":"https://openalex.org/C157922185","wikidata":"https://www.wikidata.org/wiki/Q173198","display_name":"Logic synthesis","level":3,"score":0.4805920124053955},{"id":"https://openalex.org/C131017901","wikidata":"https://www.wikidata.org/wiki/Q170451","display_name":"Logic gate","level":2,"score":0.43362003564834595},{"id":"https://openalex.org/C2983435990","wikidata":"https://www.wikidata.org/wiki/Q22725","display_name":"Network routing","level":3,"score":0.41228634119033813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2318142056465149},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20668020844459534},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.17376208305358887}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccd58817.2023.00057","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccd58817.2023.00057","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 41st International Conference on Computer Design (ICCD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320316083","display_name":"Tencent","ror":"https://ror.org/00hhjss72"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1980040075","https://openalex.org/W2770858089","https://openalex.org/W2794046273","https://openalex.org/W2801537247","https://openalex.org/W2982506612","https://openalex.org/W2992137891","https://openalex.org/W3013938122","https://openalex.org/W3109579920","https://openalex.org/W3125953074","https://openalex.org/W3127733006","https://openalex.org/W3171752851","https://openalex.org/W3213615259","https://openalex.org/W4200239775","https://openalex.org/W4210938977","https://openalex.org/W4226492646","https://openalex.org/W4231151455","https://openalex.org/W4235923234","https://openalex.org/W4248136059","https://openalex.org/W4296246734","https://openalex.org/W4312121007","https://openalex.org/W4320854859","https://openalex.org/W6849643416"],"related_works":["https://openalex.org/W2075067217","https://openalex.org/W4254709952","https://openalex.org/W2026034687","https://openalex.org/W1687060458","https://openalex.org/W1976154696","https://openalex.org/W2098419840","https://openalex.org/W2353466952","https://openalex.org/W2609535666","https://openalex.org/W4256116802","https://openalex.org/W2117492357"],"abstract_inverted_index":{"A":[0],"typical":[1],"design":[2,72],"flow":[3,73],"is":[4,113],"separated":[5],"into":[6],"front-end":[7],"and":[8,20,22,132,152,163,177,201],"back-end":[9],"stages,":[10],"incurring":[11],"huge":[12],"number":[13],"of":[14,121,175,185],"iteration":[15],"loops":[16],"between":[17],"logic":[18,50,117,189],"synthesis":[19,51,63,109,190],"place":[21],"route":[23],"to":[24,44,54,85,160,182,195],"close":[25],"timing.":[26,39],"This":[27],"has":[28],"been":[29],"even":[30],"worse":[31],"in":[32,48,65,101,173],"advanced":[33],"technology":[34],"where":[35,79],"wire":[36],"delay":[37],"dominates":[38],"It":[40],"becomes":[41],"increasingly":[42],"important":[43],"integrate":[45],"physical":[46],"awareness":[47,120],"the":[49,61,70,102,139,164,186,204],"optimization":[52,118],"processes":[53],"achieve":[55],"better":[56,196],"timing":[57,98,205],"correlations.":[58],"To":[59],"tackle":[60],"physically-aware":[62,108],"challenges,":[64],"this":[66],"paper,":[67],"we":[68],"formulate":[69],"whole":[71],"as":[74],"a":[75,94,106,183],"multi-stage":[76],"search":[77,81,88,130,141],"problem,":[78],"informed":[80],"algorithms":[82,131],"are":[83],"utilized":[84],"perform":[86],"efficient":[87,116],"with":[89,119,128],"additional":[90],"guidance.":[91],"By":[92],"incorporating":[93],"newly-developed":[95],"learning-based":[96,133],"routing-aware":[97],"prediction":[99],"model":[100],"inform":[103],"value":[104],"function,":[105],"delay-driven":[107],"methodology":[110],"called":[111],"DDPAS":[112,143,169,193],"proposed,":[114],"enabling":[115],"final":[122,197],"routed":[123],"design.":[124],"The":[125],"framework":[126],"pairs":[127],"various":[129],"strategies.":[134],"Evaluation":[135],"results":[136],"show":[137],"that":[138],"greedy":[140],"based":[142,168],"improves":[144],"total":[145],"negative":[146],"slack":[147],"(TNS)":[148],"by":[149],"over":[150,154],"58%":[151],"achieves":[153],"7%":[155],"power":[156,179],"savings":[157,180],"when":[158],"compared":[159,181],"its":[161],"counterpart,":[162],"reinforcement":[165],"learning":[166],"(RL)":[167],"delivers":[170],"65.6%":[171],"improvement":[172],"terms":[174],"TNS":[176],"12.1%":[178],"state":[184],"art":[187],"RL-based":[188],"framework.":[191],"Overall,":[192],"yields":[194],"QoR":[198],"after":[199],"routing":[200],"significantly":[202],"reduces":[203],"closure":[206],"cycles.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2025-10-10T00:00:00"}
