{"id":"https://openalex.org/W4410583062","doi":"https://doi.org/10.23919/date64628.2025.10992790","title":"Dancer: Dynamic Compression and Quantization Architecture for Deep Graph Convolutional Network","display_name":"Dancer: Dynamic Compression and Quantization Architecture for Deep Graph Convolutional Network","publication_year":2025,"publication_date":"2025-03-31","ids":{"openalex":"https://openalex.org/W4410583062","doi":"https://doi.org/10.23919/date64628.2025.10992790"},"language":"en","primary_location":{"id":"doi:10.23919/date64628.2025.10992790","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date64628.2025.10992790","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Design, Automation &amp;amp; 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/A5111265752","display_name":"Yunhao Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yunhao Dong","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016512001","display_name":"Zhaoyu Zhong","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoyu Zhong","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045425634","display_name":"Yi Wang","orcid":"https://orcid.org/0000-0002-9408-2267"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Wang","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044419677","display_name":"Chenlin Ma","orcid":"https://orcid.org/0000-0002-0497-123X"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenlin Ma","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100417411","display_name":"Tianyu Wang","orcid":"https://orcid.org/0000-0001-7030-1990"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyu Wang","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5111265752"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":2.8599,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.90917205,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9836000204086304,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9836000204086304,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9448000192642212,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9241999983787537,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7052558064460754},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.6543470621109009},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.516398012638092},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4948684573173523},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.42889273166656494},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39718854427337646},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32150745391845703},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20934021472930908}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7052558064460754},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6543470621109009},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.516398012638092},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4948684573173523},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.42889273166656494},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39718854427337646},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32150745391845703},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20934021472930908},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/date64628.2025.10992790","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date64628.2025.10992790","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Design, Automation &amp;amp; Test in Europe Conference (DATE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1512015899","display_name":null,"funder_award_id":"62122056,62102263,U23B2040","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7247962969","display_name":null,"funder_award_id":"2017B030314073","funder_id":"https://openalex.org/F4320329236","funder_display_name":"Key Laboratory of Popular Type of High-performance Computer of Guangdong Province"},{"id":"https://openalex.org/G8513502522","display_name":null,"funder_award_id":"2022A1515010180","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329236","display_name":"Key Laboratory of Popular Type of High-performance Computer of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1512387364","https://openalex.org/W2945827377","https://openalex.org/W3000310304","https://openalex.org/W3006586535","https://openalex.org/W3017228913","https://openalex.org/W3041085747","https://openalex.org/W3157609068","https://openalex.org/W4290972952","https://openalex.org/W4327503237","https://openalex.org/W4360831960","https://openalex.org/W4360831975","https://openalex.org/W4381327268","https://openalex.org/W4382202870","https://openalex.org/W4382203217","https://openalex.org/W4386763970","https://openalex.org/W4386764001","https://openalex.org/W4389166781","https://openalex.org/W4390097869","https://openalex.org/W4393407116","https://openalex.org/W4399909008","https://openalex.org/W6699364125","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6754929296","https://openalex.org/W6767582755"],"related_works":["https://openalex.org/W4391621807","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391621790","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W2947043951","https://openalex.org/W4399188509"],"abstract_inverted_index":{"Graph":[0],"Convolutional":[1],"Networks":[2],"(GCNs)":[3],"have":[4,21],"been":[5],"widely":[6],"applied":[7],"in":[8],"fields":[9],"such":[10],"as":[11],"social":[12],"network":[13],"analysis":[14,142],"and":[15,45,70,80,110,123,158,180],"recommendation":[16],"systems.":[17],"Recently,":[18],"deep":[19,35,86],"GCNs":[20,36,58,79],"emerged,":[22],"enabling":[23,60],"the":[24,104,136,156],"exploration":[25],"of":[26,135,143,182],"deeper":[27],"hidden":[28],"information.":[29],"Compared":[30],"to":[31,42,128,153,169],"traditional":[32],"shallow":[33,78],"GCNs,":[34],"feature":[37],"significantly":[38,107],"more":[39],"layers,":[40],"leading":[41],"considerable":[43],"computational":[44,157],"data":[46,65,101,130,159],"movement":[47,102],"challenges.":[48],"Processing-In-Memory":[49],"(PIM)":[50],"offers":[51],"a":[52,117,124,140,149],"promising":[53],"solution":[54],"for":[55],"efficiently":[56],"handling":[57],"by":[59],"near-data":[61],"computation,":[62],"thus":[63],"reducing":[64,111],"transfer":[66,160],"between":[67,162],"processing":[68],"units":[69],"memory.":[71],"However,":[72],"previous":[73],"work":[74],"mainly":[75],"focused":[76],"on":[77,186],"has":[81],"shown":[82],"limited":[83],"performance":[84],"with":[85],"GCNs.":[87],"In":[88],"this":[89],"paper,":[90],"we":[91,115,147],"present":[92],"Dancer,":[93],"an":[94],"innovative":[95],"PIM-based":[96],"GCN":[97],"accelerator.":[98],"Dancer":[99,173],"optimizes":[100],"during":[103],"inference":[105],"process,":[106],"improving":[108],"efficiency":[109],"energy":[112,178],"consumption.":[113],"Specifically,":[114],"introduce":[116],"novel":[118],"compressed":[119],"graph":[120],"storage":[121],"architecture":[122],"dynamic":[125],"quantization":[126],"technique":[127],"minimize":[129],"transfers":[131],"at":[132],"each":[133],"layer":[134],"GCN.":[137],"Additionally,":[138],"through":[139],"detailed":[141],"weight":[144],"dynamics":[145],"changes,":[146],"propose":[148],"sparsity":[150],"propagation":[151],"strategy":[152],"further":[154],"alleviate":[155],"burden":[161],"layers.":[163],"Experimental":[164],"results":[165],"demonstrate":[166],"that,":[167],"compared":[168],"current":[170],"state-of-the-art":[171],"methods,":[172],"achieves":[174],"3.7\u00d7":[175],"speedup,":[176],"7.6\u00d7":[177],"efficiency,":[179],"reduces":[181],"9.6\u00d7":[183],"DRAM":[184],"access":[185],"average.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
