{"id":"https://openalex.org/W2724984265","doi":"https://doi.org/10.1145/3205289.3205315","title":"On Optimizing Distributed Tucker Decomposition for Sparse Tensors","display_name":"On Optimizing Distributed Tucker Decomposition for Sparse Tensors","publication_year":2018,"publication_date":"2018-06-12","ids":{"openalex":"https://openalex.org/W2724984265","doi":"https://doi.org/10.1145/3205289.3205315","mag":"2724984265"},"language":"en","primary_location":{"id":"doi:10.1145/3205289.3205315","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3205289.3205315","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 International Conference on Supercomputing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1804.09494","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008813690","display_name":"Venkatesan T. Chakaravarthy","orcid":"https://orcid.org/0000-0002-9422-7243"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Venkatesan T. Chakaravarthy","raw_affiliation_strings":["IBM Research","IBM research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]},{"raw_affiliation_string":"IBM research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090972683","display_name":"Jee Choi","orcid":"https://orcid.org/0000-0002-6938-8221"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jee W. Choi","raw_affiliation_strings":["IBM Research","IBM research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]},{"raw_affiliation_string":"IBM research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109877611","display_name":"Douglas J. Joseph","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Douglas J. Joseph","raw_affiliation_strings":["IBM Research","IBM research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]},{"raw_affiliation_string":"IBM research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036823591","display_name":"Prakash Murali","orcid":"https://orcid.org/0000-0003-3378-8589"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prakash Murali","raw_affiliation_strings":["Princeton University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052352628","display_name":"Shivmaran S. Pandian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shivmaran S. Pandian","raw_affiliation_strings":["IBM Research","IBM research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]},{"raw_affiliation_string":"IBM research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033885850","display_name":"Yogish Sabharwal","orcid":"https://orcid.org/0009-0002-5053-2059"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yogish Sabharwal","raw_affiliation_strings":["IBM Research","IBM research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]},{"raw_affiliation_string":"IBM research","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104093269","display_name":"Dheeraj Sreedhar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dheeraj Sreedhar","raw_affiliation_strings":["IBM Research","IBM research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]},{"raw_affiliation_string":"IBM research","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"374","last_page":"384"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10792","display_name":"Matrix Theory and Algorithms","score":0.9585000276565552,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9562000036239624,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/tucker-decomposition","display_name":"Tucker decomposition","score":0.7363059520721436},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.731920599937439},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.7164625525474548},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7149548530578613},{"id":"https://openalex.org/keywords/hypergraph","display_name":"Hypergraph","score":0.6503961086273193},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6299484968185425},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.5961220860481262},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5812582969665527},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.48957642912864685},{"id":"https://openalex.org/keywords/running-time","display_name":"Running time","score":0.4535183012485504},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45163944363594055},{"id":"https://openalex.org/keywords/execution-time","display_name":"Execution time","score":0.4468037188053131},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.44557714462280273},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.4376779794692993},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3602520823478699},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3257597088813782},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.25908464193344116},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22338151931762695},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.11901146173477173}],"concepts":[{"id":"https://openalex.org/C42704193","wikidata":"https://www.wikidata.org/wiki/Q7851097","display_name":"Tucker decomposition","level":4,"score":0.7363059520721436},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.731920599937439},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.7164625525474548},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7149548530578613},{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.6503961086273193},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6299484968185425},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.5961220860481262},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5812582969665527},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.48957642912864685},{"id":"https://openalex.org/C3017489831","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Running time","level":2,"score":0.4535183012485504},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45163944363594055},{"id":"https://openalex.org/C2989134064","wikidata":"https://www.wikidata.org/wiki/Q288510","display_name":"Execution time","level":2,"score":0.4468037188053131},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.44557714462280273},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.4376779794692993},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3602520823478699},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3257597088813782},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.25908464193344116},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22338151931762695},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.11901146173477173},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3205289.3205315","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3205289.3205315","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 International Conference on Supercomputing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1804.09494","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1804.09494","pdf_url":"https://arxiv.org/pdf/1804.09494","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2724984265","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1707.05594.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1804.09494","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1804.09494","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1804.09494","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1804.09494","pdf_url":"https://arxiv.org/pdf/1804.09494","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2724984265.pdf","grobid_xml":"https://content.openalex.org/works/W2724984265.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1429947488","https://openalex.org/W1574504252","https://openalex.org/W1823244711","https://openalex.org/W1963826206","https://openalex.org/W2000215628","https://openalex.org/W2004642969","https://openalex.org/W2013912476","https://openalex.org/W2018282388","https://openalex.org/W2024165284","https://openalex.org/W2055913665","https://openalex.org/W2058812752","https://openalex.org/W2079487069","https://openalex.org/W2086022711","https://openalex.org/W2095729436","https://openalex.org/W2099293709","https://openalex.org/W2103392911","https://openalex.org/W2108138101","https://openalex.org/W2108207327","https://openalex.org/W2119511382","https://openalex.org/W2121739212","https://openalex.org/W2481767403","https://openalex.org/W2523567745","https://openalex.org/W2541878878","https://openalex.org/W2611804663","https://openalex.org/W2724545582","https://openalex.org/W2739912219","https://openalex.org/W2741701794","https://openalex.org/W2892981087","https://openalex.org/W2952647294","https://openalex.org/W3101742238"],"related_works":["https://openalex.org/W2964051974","https://openalex.org/W3158164473","https://openalex.org/W2103329426","https://openalex.org/W2787128677","https://openalex.org/W2783429390","https://openalex.org/W2362761589","https://openalex.org/W3125745477","https://openalex.org/W2921917212","https://openalex.org/W2090917733","https://openalex.org/W2466962919","https://openalex.org/W3170310817","https://openalex.org/W3138153036","https://openalex.org/W3195049185","https://openalex.org/W3175869692","https://openalex.org/W3195652320","https://openalex.org/W3098013468","https://openalex.org/W134495272","https://openalex.org/W2583301806","https://openalex.org/W2965758384","https://openalex.org/W950773855"],"abstract_inverted_index":{"The":[0,43],"Tucker":[1,26],"decomposition":[2,27],"generalizes":[3],"the":[4,13,21,25,36,48,52,58,88,101,106,115,133,141,151,160,165,172,176,181,183,189,209,212,216,228,237,246],"notion":[5],"of":[6,17,23,28,111,118,135,223,249],"Singular":[7],"Value":[8],"Decomposition":[9],"(SVD)":[10],"to":[11,203,225,236],"tensors,":[12],"higher":[14,113,169],"dimensional":[15],"analogues":[16],"matrices.":[18],"We":[19,138],"study":[20],"problem":[22],"constructing":[24],"sparse":[29],"tensors":[30,200],"on":[31,73,145,159,188,197,215],"distributed":[32],"memory":[33],"systems":[34],"via":[35],"HOOI":[37,59,96,121,152,191,217,252],"procedure,":[38],"a":[39,119,127,156,221,250],"popular":[40],"iterative":[41],"method.":[42],"scheme":[44,71,91,142,166,184,210],"used":[45,85],"for":[46,104],"distributing":[47],"input":[49],"tensor":[50],"among":[51],"processors":[53],"(MPI":[54],"ranks)":[55],"critically":[56],"influences":[57],"execution":[60,97,116,192,218,247],"time.":[61,193],"Prior":[62],"work":[63],"has":[64],"proposed":[65],"different":[66],"distribution":[67,107,129,232],"schemes:":[68],"an":[69,109],"offline":[70],"based":[72,90],"sophisticated":[74],"hypergraph":[75,89],"partitioning":[76],"method":[77],"and":[78,154,179,241],"simple,":[79],"lightweight":[80,128,239],"alternatives":[81],"that":[82,140,208],"can":[83],"be":[84],"real-time.":[86],"While":[87],"typically":[92,243],"results":[93],"in":[94],"faster":[95],"time,":[98],"being":[99],"complex,":[100],"time":[102,117,174,219,233,248],"taken":[103],"determining":[105],"is":[108,126,143,175,234,242],"order":[110],"magnitude":[112],"than":[114,245],"single":[120,251],"iteration.":[122,253],"Our":[123,194],"main":[124],"contribution":[125],"scheme,":[130],"which":[131],"achieves":[132,185],"best":[134],"both":[136],"worlds.":[137],"show":[139],"near-optimal":[144,158],"certain":[146],"fundamental":[147],"metrics":[148],"associated":[149],"with":[150],"procedure":[153],"as":[155,180],"result,":[157,182],"computational":[161],"load":[162],"(FLOPs).":[163],"Though":[164],"may":[167],"incur":[168],"communication":[170],"volume,":[171],"computation":[173],"dominant":[177],"factor":[178,222],"better":[186],"performance":[187],"overall":[190],"experimental":[195],"evaluation":[196],"large":[198],"real-life":[199],"(having":[201],"up":[202,224],"4":[204],"billion":[205],"elements)":[206],"shows":[207],"outperforms":[211],"prior":[213,238],"schemes":[214,240],"by":[220],"3x.":[226],"On":[227],"other":[229],"hand,":[230],"its":[231],"comparable":[235],"lesser":[244]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":3}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}