{"id":"https://openalex.org/W4406457791","doi":"https://doi.org/10.1109/bigdata62323.2024.10825530","title":"PUSHGNN: A Low-communication Runtime System for GNN Acceleration on Multi-GPUs","display_name":"PUSHGNN: A Low-communication Runtime System for GNN Acceleration on Multi-GPUs","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406457791","doi":"https://doi.org/10.1109/bigdata62323.2024.10825530"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5107094004","display_name":"Guoqing Xiao","orcid":"https://orcid.org/0000-0001-5008-4829"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoqing Xiao","raw_affiliation_strings":["Hunan University,College of Computer Science and Electronic Engineering,Changsha,China,410082"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hunan University,College of Computer Science and Electronic Engineering,Changsha,China,410082","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112834723","display_name":"Li Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Xia","raw_affiliation_strings":["Hunan University,College of Computer Science and Electronic Engineering,Changsha,China,410082"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hunan University,College of Computer Science and Electronic Engineering,Changsha,China,410082","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035942362","display_name":"Yuedan Chen","orcid":"https://orcid.org/0000-0001-5665-268X"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuedan Chen","raw_affiliation_strings":["Central South University,Big Data Institute,Changsha,China,410083"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Central South University,Big Data Institute,Changsha,China,410083","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016247312","display_name":"Wangdong Yang","orcid":"https://orcid.org/0000-0003-2681-7898"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wangdong Yang","raw_affiliation_strings":["Hunan University,College of Computer Science and Electronic Engineering,Changsha,China,410082"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hunan University,College of Computer Science and Electronic Engineering,Changsha,China,410082","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4078","last_page":"4085"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9929999709129333,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9929999709129333,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9926999807357788,"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/T11478","display_name":"Caching and Content Delivery","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computer-science","display_name":"Computer science","score":0.8164733648300171},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.6894540786743164},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.34473615884780884},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.059891343116760254}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8164733648300171},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.6894540786743164},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.34473615884780884},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.059891343116760254},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.800000011920929,"display_name":"Affordable and clean energy"}],"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":35,"referenced_works":["https://openalex.org/W1965830721","https://openalex.org/W1992851788","https://openalex.org/W2096029105","https://openalex.org/W2151498529","https://openalex.org/W2161902954","https://openalex.org/W2734941459","https://openalex.org/W2747329762","https://openalex.org/W2755088640","https://openalex.org/W2764075199","https://openalex.org/W2963601856","https://openalex.org/W3011293047","https://openalex.org/W3096566397","https://openalex.org/W3146824751","https://openalex.org/W3159109662","https://openalex.org/W4248722156","https://openalex.org/W4288419263","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6744271739","https://openalex.org/W6744557953","https://openalex.org/W6745537798","https://openalex.org/W6748799445","https://openalex.org/W6751796012","https://openalex.org/W6753331806","https://openalex.org/W6754929296","https://openalex.org/W6760045743","https://openalex.org/W6764171799","https://openalex.org/W6766160392","https://openalex.org/W6766978945","https://openalex.org/W6767710714","https://openalex.org/W6776488958","https://openalex.org/W6779909149","https://openalex.org/W6797677657","https://openalex.org/W6843221661"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"The":[0],"need":[1],"for":[2],"multi-GPU":[3],"platforms":[4],"in":[5],"graph":[6],"neural":[7],"networks":[8],"(GNNs)":[9],"has":[10,27],"been":[11,28],"driven":[12],"by":[13],"the":[14,22,31],"growing":[15],"size":[16],"of":[17,33],"input":[18],"graphs.":[19],"However,":[20],"although":[21],"existing":[23],"multi-gpu":[24],"GNN":[25,60,88],"framework":[26],"optimized":[29],"from":[30],"perspective":[32],"optimizing":[34],"computing":[35],"and":[36,70,93,98],"communication":[37,39,55,68],"operations,":[38],"competition":[40],"still":[41],"exists.":[42],"To":[43],"this":[44],"end,":[45],"we":[46,63],"introduce":[47],"PUSHGNN,":[48],"a":[49,65],"runtime":[50],"system":[51],"designed":[52,64],"to":[53,74],"reduce":[54,76],"overhead":[56],"across":[57],"GPUs,":[58],"boosting":[59],"performance.":[61],"Therefore,":[62],"push-based":[66],"pipeline":[67,77],"model":[69],"made":[71],"custom":[72],"tuning":[73],"significantly":[75],"contention.":[78],"Comparative":[79],"assessments":[80],"demonstrate":[81],"that":[82],"PUSHGNN":[83],"consistently":[84],"outperforms":[85],"leading":[86],"full-graph":[87],"systems":[89],"on":[90],"average":[91],"1.97\u00d7":[92],"7.57\u00d7":[94],"faster":[95],"than":[96],"MGG":[97],"MGG-UVM,":[99],"respectively.":[100]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
