{"id":"https://openalex.org/W7142610424","doi":"https://doi.org/10.1080/09540091.2026.2650981","title":"A near CXL memory processing architecture for distributed graph neural network inference and training","display_name":"A near CXL memory processing architecture for distributed graph neural network inference and training","publication_year":2026,"publication_date":"2026-03-28","ids":{"openalex":"https://openalex.org/W7142610424","doi":"https://doi.org/10.1080/09540091.2026.2650981"},"language":"en","primary_location":{"id":"doi:10.1080/09540091.2026.2650981","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2026.2650981","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2026.2650981?needAccess=true","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2026.2650981?needAccess=true","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130907651","display_name":"Haoyang Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyang Wang","raw_affiliation_strings":["School of Computer Science, Northwestern Polytechnical University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Northwestern Polytechnical University","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056711524","display_name":"Shengbing ZHANG","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengbing Zhang","raw_affiliation_strings":["School of Computer Science, Northwestern Polytechnical University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Northwestern Polytechnical University","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017058932","display_name":"Xiaoya Fan","orcid":"https://orcid.org/0000-0002-6190-8077"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoya Fan","raw_affiliation_strings":["School of Computer Science, Northwestern Polytechnical University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Northwestern Polytechnical University","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5130886155","display_name":"Meng Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Meng Zhang","raw_affiliation_strings":["School of Computer Science, Northwestern Polytechnical University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Northwestern Polytechnical University","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5130886155"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":{"value":1270,"currency":"USD","value_usd":1270},"apc_paid":{"value":1270,"currency":"USD","value_usd":1270},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33949218,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"38","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.6711000204086304,"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":0.6711000204086304,"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":0.1648000031709671,"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/T10320","display_name":"Neural Networks and Applications","score":0.017400000244379044,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6202999949455261},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5655999779701233},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5113999843597412},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.49950000643730164},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.43650001287460327},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.36739999055862427},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3472000062465668}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8664000034332275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6251999735832214},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6202999949455261},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5655999779701233},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5113999843597412},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.49950000643730164},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.43650001287460327},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4147999882698059},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.36739999055862427},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3472000062465668},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.3386000096797943},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3215999901294708},{"id":"https://openalex.org/C8521452","wikidata":"https://www.wikidata.org/wiki/Q203790","display_name":"Connectionism","level":3,"score":0.2870999872684479},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.28690001368522644},{"id":"https://openalex.org/C157170001","wikidata":"https://www.wikidata.org/wiki/Q4781507","display_name":"Applications of artificial intelligence","level":2,"score":0.2833999991416931},{"id":"https://openalex.org/C2779602883","wikidata":"https://www.wikidata.org/wiki/Q15544750","display_name":"Memory architecture","level":2,"score":0.2551000118255615},{"id":"https://openalex.org/C98025372","wikidata":"https://www.wikidata.org/wiki/Q477538","display_name":"Systems architecture","level":3,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/09540091.2026.2650981","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2026.2650981","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2026.2650981?needAccess=true","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1080/09540091.2026.2650981","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2026.2650981","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2026.2650981?needAccess=true","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7142610424.pdf","grobid_xml":"https://content.openalex.org/works/W7142610424.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W2034861439","https://openalex.org/W2296407087","https://openalex.org/W2807021761","https://openalex.org/W2914721378","https://openalex.org/W2951050019","https://openalex.org/W2963601856","https://openalex.org/W2979719709","https://openalex.org/W3207399097","https://openalex.org/W4282011755","https://openalex.org/W4285113882","https://openalex.org/W4318328413","https://openalex.org/W4392806407"],"related_works":[],"abstract_inverted_index":{"Distributed":[0],"Graph":[1],"Neural":[2],"Networks":[3],"(GNNs)":[4],"require":[5],"efficient":[6],"handling":[7],"of":[8,60],"both":[9],"fine-grained":[10,61],"memory":[11,62],"accesses":[12],"and":[13,34,39,83,104,125,132],"cross":[14,88],"memory-device":[15,89],"communication,":[16,78],"particularly":[17],"when":[18],"scaling":[19],"to":[20,28,120],"large":[21],"graphs.":[22],"However,":[23],"existing":[24],"acceleration":[25,102,112],"solutions":[26],"fail":[27],"adequately":[29],"address":[30],"low":[31],"bandwidth":[32,73],"utilization":[33],"scalability":[35],"across":[36],"different":[37],"models":[38,124],"graph":[40],"sizes.":[41],"In":[42],"this":[43],"paper,":[44],"we":[45,79],"present":[46],"OptGNN,":[47],"a":[48,66],"scalable":[49],"heterogeneous":[50],"distributed":[51,100,110],"architecture":[52,113],"tailored":[53],"for":[54],"GNNs.":[55],"OptGNN":[56,93],"addresses":[57],"the":[58,116],"challenges":[59],"access":[63],"by":[64],"incorporating":[65],"near-memory":[67],"processing":[68],"mechanism,":[69],"which":[70],"improves":[71],"internal":[72],"utilization.":[74,135],"To":[75],"optimize":[76],"external":[77],"introduce":[80],"data":[81,90],"packing":[82],"scheduling":[84],"strategies":[85],"that":[86],"enhance":[87],"transfer":[91],"efficiency.":[92],"achieves":[94],"5.7x":[95],"performance":[96,106],"improvement":[97,107],"over":[98,108],"baseline":[99],"GNN":[101,111,123],"methods":[103],"1.29x":[105],"SOTA":[109],"CLAY.":[114],"Additionally,":[115],"system":[117],"is":[118],"designed":[119],"support":[121],"various":[122],"large-scale":[126],"graphs":[127],"while":[128],"ensuring":[129],"load":[130],"balancing":[131],"high":[133],"hardware":[134]},"counts_by_year":[],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2026-03-30T00:00:00"}