{"id":"https://openalex.org/W7134893807","doi":"https://doi.org/10.1109/asp-dac66049.2026.11420333","title":"HLS-Timer: Fine-Grained Path-Level Timing Estimation for High-Level Synthesis","display_name":"HLS-Timer: Fine-Grained Path-Level Timing Estimation for High-Level Synthesis","publication_year":2026,"publication_date":"2026-01-19","ids":{"openalex":"https://openalex.org/W7134893807","doi":"https://doi.org/10.1109/asp-dac66049.2026.11420333"},"language":null,"primary_location":{"id":"doi:10.1109/asp-dac66049.2026.11420333","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac66049.2026.11420333","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 31st Asia and South Pacific Design Automation Conference (ASP-DAC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5128761546","display_name":"Zibo Hu","orcid":null},"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":"Zibo Hu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128738689","display_name":"Zhe Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Lin","raw_affiliation_strings":["Sun Yat-sen University,Shenzhen Campus"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,Shenzhen Campus","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128779168","display_name":"Renjing Hou","orcid":null},"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":"Renjing Hou","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114232632","display_name":"Xingyu QIN","orcid":null},"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":"Xingyu Qin","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing","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,Beijing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128729678","display_name":"Kang Zhao","orcid":null},"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,Beijing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15665914,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"496","last_page":"502"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10904","display_name":"Embedded Systems Design Techniques","score":0.2612999975681305,"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"}},"topics":[{"id":"https://openalex.org/T10904","display_name":"Embedded Systems Design Techniques","score":0.2612999975681305,"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"}},{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.18070000410079956,"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"}},{"id":"https://openalex.org/T10363","display_name":"Low-power high-performance VLSI design","score":0.04569999873638153,"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/estimation","display_name":"Estimation","score":0.4090999960899353},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.3046000003814697},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.2849999964237213},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.2628999948501587},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.2540000081062317}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5108000040054321},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4090999960899353},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3840000033378601},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2849999964237213},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2745000123977661},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27399998903274536},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.2498999983072281}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asp-dac66049.2026.11420333","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac66049.2026.11420333","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 31st Asia and South Pacific Design Automation Conference (ASP-DAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W2012114780","https://openalex.org/W2889669826","https://openalex.org/W2985324865","https://openalex.org/W4210938977","https://openalex.org/W4229673714","https://openalex.org/W4283730710","https://openalex.org/W4298385411","https://openalex.org/W4312729670","https://openalex.org/W4385245566","https://openalex.org/W4388040391","https://openalex.org/W4388071571","https://openalex.org/W4389166667"],"related_works":[],"abstract_inverted_index":{"Electronic":[0],"Design":[1],"Automation":[2],"(EDA)":[3],"requires":[4],"early":[5],"stage":[6],"timing":[7,14,31,46,68,87,102,127,172],"guidance":[8],"to":[9,125,176],"maximize":[10],"optimization":[11],"potential.":[12],"Accurate":[13],"estimation":[15,88,150],"is":[16],"essential":[17],"in":[18,34,65,70,147,170],"the":[19,99,114],"High-Level":[20],"Synthesis":[21],"(HLS)":[22],"stage.":[23],"However,":[24],"current":[25],"HLS":[26,71,115],"tools":[27],"often":[28],"produce":[29],"inaccurate":[30],"predictions,":[32],"resulting":[33],"unmet":[35],"performance":[36],"targets.":[37],"While":[38],"post-synthesis":[39],"EDA":[40],"tool":[41],"chains":[42],"can":[43],"provide":[44,130],"precise":[45],"analysis,":[47],"their":[48],"exhaustive":[49],"methodologies":[50],"are":[51],"prohibitively":[52],"time-consuming":[53],"and":[54,79,129,181],"computationally":[55],"expensive.":[56],"Recent":[57],"machine":[58],"learning":[59],"approaches":[60],"have":[61],"demonstrated":[62],"promising":[63],"results":[64,136],"predicting":[66],"design-level":[67,171],"metrics":[69],"designs,":[72],"such":[73],"as":[74],"Worst":[75],"Negative":[76],"Slack":[77],"(WNS)":[78],"Critical":[80],"Path":[81],"(CP)":[82],"delay.":[83],"Nevertheless,":[84],"fine-grained,":[85],"path-level":[86,101,148],"remains":[89],"an":[90],"unresolved":[91],"challenge.":[92],"In":[93],"this":[94],"work,":[95],"we":[96],"present":[97],"HLS-Timer,":[98],"first":[100],"estimator":[103],"for":[104,179,184],"HLS.":[105],"The":[106],"proposed":[107],"framework":[108],"employs":[109],"a":[110],"graph-based":[111],"representation":[112],"of":[113],"design,":[116],"integrating":[117],"local":[118],"structural":[119],"features":[120],"with":[121],"global":[122],"contextual":[123],"information":[124],"model":[126],"paths":[128],"accurate,":[131],"finegrained":[132],"delay":[133,149],"predictions.":[134],"Experimental":[135],"demonstrate":[137],"that":[138],"on":[139],"previously":[140],"unseen":[141],"designs":[142],"HLS-Timer":[143],"achieves":[144],"exceptional":[145],"accuracy":[146],"(Pearson":[151],"$\\mathbf{R}=\\mathbf{0.":[152],"9":[153],"4},":[154],"\\mathbf{R}^{\\mathbf{2}}":[155],"=0.93$,":[156],"MAPE":[157,175],"$=18.96":[158],"\\%$),":[159],"highlighting":[160],"its":[161],"strong":[162],"generalization":[163],"capability.":[164],"Furthermore,":[165],"it":[166],"surpasses":[167],"state-of-the-art":[168],"baselines":[169],"prediction,":[173],"reducing":[174],"$9.97":[177],"\\%$":[178,183],"WNS":[180],"$6.79":[182],"CP":[185],"delays.":[186]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-03-12T00:00:00"}