{"id":"https://openalex.org/W2070929497","doi":"https://doi.org/10.1145/2755573.2755591","title":"Space and Time Efficient Parallel Graph Decomposition, Clustering, and Diameter Approximation","display_name":"Space and Time Efficient Parallel Graph Decomposition, Clustering, and Diameter Approximation","publication_year":2015,"publication_date":"2015-06-12","ids":{"openalex":"https://openalex.org/W2070929497","doi":"https://doi.org/10.1145/2755573.2755591","mag":"2070929497"},"language":"en","primary_location":{"id":"doi:10.1145/2755573.2755591","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2755573.2755591","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 symposium on Parallelism in Algorithms and Architectures","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/A5054188110","display_name":"Matteo Ceccarello","orcid":"https://orcid.org/0000-0003-2783-0218"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Matteo Ceccarello","raw_affiliation_strings":["Department of Information Engineering, University of Padova, Padova, Italy","Department of Information Engineering; University of Padova; Padova; Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, University of Padova, Padova, Italy","institution_ids":["https://openalex.org/I138689650"]},{"raw_affiliation_string":"Department of Information Engineering; University of Padova; Padova; Italy","institution_ids":["https://openalex.org/I138689650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036587129","display_name":"Andrea Pietracaprina","orcid":"https://orcid.org/0000-0002-9189-9618"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Andrea Pietracaprina","raw_affiliation_strings":["Department of Information Engineering, University of Padova, Padova, Italy","Department of Information Engineering; University of Padova; Padova; Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, University of Padova, Padova, Italy","institution_ids":["https://openalex.org/I138689650"]},{"raw_affiliation_string":"Department of Information Engineering; University of Padova; Padova; Italy","institution_ids":["https://openalex.org/I138689650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048624224","display_name":"Geppino Pucci","orcid":"https://orcid.org/0000-0001-9189-6938"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Geppino Pucci","raw_affiliation_strings":["Department of Information Engineering, University of Padova, Padova, Italy","Department of Information Engineering; University of Padova; Padova; Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, University of Padova, Padova, Italy","institution_ids":["https://openalex.org/I138689650"]},{"raw_affiliation_string":"Department of Information Engineering; University of Padova; Padova; Italy","institution_ids":["https://openalex.org/I138689650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028869858","display_name":"Eli Upfal","orcid":"https://orcid.org/0000-0002-9321-9460"},"institutions":[{"id":"https://openalex.org/I27804330","display_name":"Brown University","ror":"https://ror.org/05gq02987","country_code":"US","type":"education","lineage":["https://openalex.org/I27804330"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eli Upfal","raw_affiliation_strings":["Brown University, Providence, RI, USA"],"affiliations":[{"raw_affiliation_string":"Brown University, Providence, RI, USA","institution_ids":["https://openalex.org/I27804330"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5054188110"],"corresponding_institution_ids":["https://openalex.org/I138689650"],"apc_list":null,"apc_paid":null,"fwci":2.4049,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.88497217,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"182","last_page":"191"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9945999979972839,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.993399977684021,"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/disjoint-sets","display_name":"Disjoint sets","score":0.6533822417259216},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.5660300254821777},{"id":"https://openalex.org/keywords/sublinear-function","display_name":"Sublinear function","score":0.5347349643707275},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5130287408828735},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5030948519706726},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4414674937725067},{"id":"https://openalex.org/keywords/modular-decomposition","display_name":"Modular decomposition","score":0.4414274990558624},{"id":"https://openalex.org/keywords/linear-space","display_name":"Linear space","score":0.4296509027481079},{"id":"https://openalex.org/keywords/pathwidth","display_name":"Pathwidth","score":0.3964530825614929},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.3944389820098877},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36632871627807617},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3598576486110687},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.3521639108657837},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3433862328529358},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3266296088695526},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.1490909457206726},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.09173020720481873}],"concepts":[{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.6533822417259216},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.5660300254821777},{"id":"https://openalex.org/C117160843","wikidata":"https://www.wikidata.org/wiki/Q338652","display_name":"Sublinear function","level":2,"score":0.5347349643707275},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5130287408828735},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5030948519706726},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4414674937725067},{"id":"https://openalex.org/C187407849","wikidata":"https://www.wikidata.org/wiki/Q6889712","display_name":"Modular decomposition","level":5,"score":0.4414274990558624},{"id":"https://openalex.org/C176370821","wikidata":"https://www.wikidata.org/wiki/Q1826459","display_name":"Linear space","level":2,"score":0.4296509027481079},{"id":"https://openalex.org/C43517604","wikidata":"https://www.wikidata.org/wiki/Q7144893","display_name":"Pathwidth","level":4,"score":0.3964530825614929},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.3944389820098877},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36632871627807617},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3598576486110687},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.3521639108657837},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3433862328529358},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3266296088695526},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.1490909457206726},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.09173020720481873}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/2755573.2755591","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2755573.2755591","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 symposium on Parallelism in Algorithms and Architectures","raw_type":"proceedings-article"},{"id":"pmh:oai:alma.39UBZ_INST:11251683950001241","is_oa":false,"landing_page_url":"https://dl.acm.org/doi/abs/10.1145/2755573.2755591","pdf_url":null,"source":{"id":"https://openalex.org/S4210197018","display_name":"View","issn_l":"2688-268X","issn":["2688-268X","2688-3988"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:www.research.unipd.it:11577/3156391","is_oa":false,"landing_page_url":"http://hdl.handle.net/11577/3156391","pdf_url":null,"source":{"id":"https://openalex.org/S4377196283","display_name":"Research Padua  Archive (University of Padua)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138689650","host_organization_name":"University of Padua","host_organization_lineage":["https://openalex.org/I138689650"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321873","display_name":"Ministero dell\u2019Istruzione, dell\u2019Universit\u00e0 e della Ricerca","ror":"https://ror.org/0166hxq48"},{"id":"https://openalex.org/F4320321966","display_name":"Universit\u00e0 degli Studi di Padova","ror":"https://ror.org/00240q980"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1503698146","https://openalex.org/W1538106700","https://openalex.org/W1804827942","https://openalex.org/W1896986493","https://openalex.org/W1969080501","https://openalex.org/W1973264045","https://openalex.org/W1996194724","https://openalex.org/W2025919541","https://openalex.org/W2034616054","https://openalex.org/W2040615703","https://openalex.org/W2040660972","https://openalex.org/W2044124066","https://openalex.org/W2051586153","https://openalex.org/W2075862701","https://openalex.org/W2085630237","https://openalex.org/W2092938419","https://openalex.org/W2097187365","https://openalex.org/W2097747425","https://openalex.org/W2131975293","https://openalex.org/W2140030920","https://openalex.org/W2142266972","https://openalex.org/W2151095918","https://openalex.org/W2169036209","https://openalex.org/W2173213060","https://openalex.org/W2250978763","https://openalex.org/W2611804663","https://openalex.org/W3101158212"],"related_works":["https://openalex.org/W4376639521","https://openalex.org/W4298333731","https://openalex.org/W2031276298","https://openalex.org/W2147332298","https://openalex.org/W2952233599","https://openalex.org/W1566820354","https://openalex.org/W577041502","https://openalex.org/W4299811717","https://openalex.org/W2093949146","https://openalex.org/W1892973443"],"abstract_inverted_index":{"We":[0,49],"develop":[1],"a":[2,36,75,83,143,160],"novel":[3],"parallel":[4,56,108,132,140],"decomposition":[5],"strategy":[6,34],"for":[7,89,97,116,134,142,159],"unweighted,":[8],"undirected":[9],"graphs,":[10,147],"based":[11],"on":[12,39,164,169,178],"growing":[13],"disjoint":[14],"connected":[15],"clusters":[16,44],"from":[17,23],"batches":[18],"of":[19,43,54,125,146],"centers":[20],"progressively":[21],"selected":[22],"yet":[24],"uncovered":[25],"nodes.":[26],"With":[27],"respect":[28],"to":[29,82,183],"similar":[30],"previous":[31],"decompositions,":[32],"our":[33,55,126,156],"exercises":[35],"tighter":[37],"control":[38],"both":[40,68],"the":[41,98,103,107,114,123,130,153],"number":[42],"and":[45,63,79,106,176],"their":[46,174],"maximum":[47],"radius.":[48],"present":[50],"two":[51],"important":[52],"applications":[53],"graph":[57],"decomposition:":[58],"(1)":[59],"$k$-center":[60],"clustering":[61],"approximation;":[62],"(2)":[64],"diameter":[65,115],"approximation.":[66],"In":[67],"cases,":[69],"we":[70,167],"obtain":[71],"algorithms":[72,157],"which":[73,137,172],"feature":[74],"polylogarithmic":[76],"approximation":[77],"factor":[78],"are":[80,129],"amenable":[81],"distributed":[84],"implementation":[85,163],"that":[86],"is":[87,100,110],"geared":[88],"massive":[90],"(long-diameter)":[91],"graphs.":[92],"The":[93],"total":[94],"space":[95],"needed":[96],"computation":[99],"linear":[101,150],"in":[102,113],"problem":[104],"size,":[105],"depth":[109],"substantially":[111],"sublinear":[112],"graphs":[117,180],"with":[118],"low":[119],"doubling":[120],"dimension.":[121],"To":[122],"best":[124],"knowledge,":[127],"ours":[128],"first":[131],"approximations":[133],"these":[135],"problems":[136],"achieve":[138],"sub-diameter":[139],"time,":[141],"relevant":[144],"class":[145],"using":[148],"only":[149],"space.":[151],"Besides":[152],"theoretical":[154],"guarantees,":[155],"allow":[158],"very":[161],"simple":[162],"clustered":[165],"architectures:":[166],"report":[168],"extensive":[170],"experiments":[171],"demonstrate":[173],"effectiveness":[175],"efficiency":[177],"large":[179],"as":[181],"compared":[182],"alternative":[184],"known":[185],"approaches.":[186]},"counts_by_year":[{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}