{"id":"https://openalex.org/W4221045583","doi":"https://doi.org/10.1145/3503221.3508435","title":"Rethinking graph data placement for graph neural network training on multiple GPUs","display_name":"Rethinking graph data placement for graph neural network training on multiple GPUs","publication_year":2022,"publication_date":"2022-03-28","ids":{"openalex":"https://openalex.org/W4221045583","doi":"https://doi.org/10.1145/3503221.3508435"},"language":"en","primary_location":{"id":"doi:10.1145/3503221.3508435","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503221.3508435","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming","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/A5025805788","display_name":"Shihui Song","orcid":"https://orcid.org/0009-0007-9426-8591"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shihui Song","raw_affiliation_strings":["The University of Iowa"],"affiliations":[{"raw_affiliation_string":"The University of Iowa","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001339397","display_name":"Peng Jiang","orcid":"https://orcid.org/0000-0002-9266-0780"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peng Jiang","raw_affiliation_strings":["The University of Iowa"],"affiliations":[{"raw_affiliation_string":"The University of Iowa","institution_ids":["https://openalex.org/I126307644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5025805788"],"corresponding_institution_ids":["https://openalex.org/I126307644"],"apc_list":null,"apc_paid":null,"fwci":0.302,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.51916733,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"455","last_page":"456"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9993000030517578,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9991000294685364,"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/T11478","display_name":"Caching and Content Delivery","score":0.9944999814033508,"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":0.8449693918228149},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.583468496799469},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.5089430809020996},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.45531851053237915},{"id":"https://openalex.org/keywords/graph-database","display_name":"Graph database","score":0.4294179081916809},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41224777698516846},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3512434959411621},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24185049533843994},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.12563541531562805}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8449693918228149},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.583468496799469},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5089430809020996},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.45531851053237915},{"id":"https://openalex.org/C176225458","wikidata":"https://www.wikidata.org/wiki/Q595971","display_name":"Graph database","level":3,"score":0.4294179081916809},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41224777698516846},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3512434959411621},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24185049533843994},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.12563541531562805}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3503221.3508435","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503221.3508435","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W3096566397","https://openalex.org/W3159953606","https://openalex.org/W4213135654"],"related_works":["https://openalex.org/W2952348651","https://openalex.org/W2375742443","https://openalex.org/W2149381099","https://openalex.org/W4200520489","https://openalex.org/W1483190388","https://openalex.org/W978295669","https://openalex.org/W3115442681","https://openalex.org/W2007838763","https://openalex.org/W2391000461","https://openalex.org/W2972311463"],"abstract_inverted_index":{"The":[0,83],"existing":[1,27,97],"Graph":[2],"Neural":[3],"Network":[4],"(GNN)":[5],"systems":[6],"adopt":[7],"graph":[8,13,70,98],"partitioning":[9,99],"to":[10,30,65],"divide":[11,66],"the":[12,26,40,44,57,69,77,96],"data":[14,32,45,71,78,91],"for":[15,39],"multi-GPU":[16],"training.":[17,54],"Although":[18],"they":[19],"support":[20],"large":[21,31],"graphs,":[22],"we":[23,38,60],"find":[24],"that":[25,76,86],"techniques":[28],"lead":[29],"loading":[33,79,92],"overhead.":[34],"In":[35],"this":[36],"work,":[37],"first":[41],"time":[42,80,93],"model":[43],"movement":[46],"overhead":[47],"among":[48],"CPU":[49],"and":[50,67],"GPUs":[51,74],"in":[52],"GNN":[53],"Based":[55],"on":[56],"performance":[58],"model,":[59],"provide":[61],"an":[62],"efficient":[63],"algorithm":[64],"distribute":[68],"onto":[72],"multiple":[73],"so":[75],"is":[81],"minimized.":[82],"experiments":[84],"show":[85],"our":[87],"technique":[88],"achieves":[89],"smaller":[90],"compared":[94],"with":[95],"methods.":[100]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}