{"id":"https://openalex.org/W1964635340","doi":"https://doi.org/10.1145/1851476.1851512","title":"GPU-based parallel householder bidiagonalization","display_name":"GPU-based parallel householder bidiagonalization","publication_year":2010,"publication_date":"2010-06-21","ids":{"openalex":"https://openalex.org/W1964635340","doi":"https://doi.org/10.1145/1851476.1851512","mag":"1964635340"},"language":"en","primary_location":{"id":"doi:10.1145/1851476.1851512","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1851476.1851512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing","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/A5068602228","display_name":"Fangbin Liu","orcid":"https://orcid.org/0000-0002-3276-0501"},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Fangbin Liu","raw_affiliation_strings":["University of Amsterdam, Kruislaan, SJ, Amsterdam, The Netherlands","University of Amsterdam, Kruislaan, SJ Amsterdam, The Netherlands#TAB#"],"affiliations":[{"raw_affiliation_string":"University of Amsterdam, Kruislaan, SJ, Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I887064364"]},{"raw_affiliation_string":"University of Amsterdam, Kruislaan, SJ Amsterdam, The Netherlands#TAB#","institution_ids":["https://openalex.org/I887064364"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073170852","display_name":"F.J. Seinstra","orcid":null},"institutions":[{"id":"https://openalex.org/I865915315","display_name":"Vrije Universiteit Amsterdam","ror":"https://ror.org/008xxew50","country_code":"NL","type":"education","lineage":["https://openalex.org/I865915315"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Frank J. Seinstra","raw_affiliation_strings":["VU University, De Boelelaan, HV, Amsterdam, The Netherlands"],"affiliations":[{"raw_affiliation_string":"VU University, De Boelelaan, HV, Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I865915315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5068602228"],"corresponding_institution_ids":["https://openalex.org/I887064364"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.05147059,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"288","last_page":"291"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9872999787330627,"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":0.9872999787330627,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9480000138282776,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8385358452796936},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.8041247129440308},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.7640658617019653},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.7241227030754089},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.6850964426994324},{"id":"https://openalex.org/keywords/lu-decomposition","display_name":"LU decomposition","score":0.5395210981369019},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.5174899101257324},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.48684781789779663},{"id":"https://openalex.org/keywords/gpu-cluster","display_name":"GPU cluster","score":0.4727257788181305},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.4615846276283264},{"id":"https://openalex.org/keywords/computational-science","display_name":"Computational science","score":0.4479522109031677},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4431619346141815},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4344737231731415},{"id":"https://openalex.org/keywords/multi-core-processor","display_name":"Multi-core processor","score":0.4269435405731201},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.41861242055892944},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40520280599594116},{"id":"https://openalex.org/keywords/cuda","display_name":"CUDA","score":0.1834683120250702},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09489551186561584},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.08225741982460022}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8385358452796936},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.8041247129440308},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.7640658617019653},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.7241227030754089},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.6850964426994324},{"id":"https://openalex.org/C123213974","wikidata":"https://www.wikidata.org/wiki/Q833089","display_name":"LU decomposition","level":4,"score":0.5395210981369019},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.5174899101257324},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.48684781789779663},{"id":"https://openalex.org/C2781335571","wikidata":"https://www.wikidata.org/wiki/Q2633544","display_name":"GPU cluster","level":3,"score":0.4727257788181305},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.4615846276283264},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.4479522109031677},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4431619346141815},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4344737231731415},{"id":"https://openalex.org/C78766204","wikidata":"https://www.wikidata.org/wiki/Q555032","display_name":"Multi-core processor","level":2,"score":0.4269435405731201},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.41861242055892944},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40520280599594116},{"id":"https://openalex.org/C2778119891","wikidata":"https://www.wikidata.org/wiki/Q477690","display_name":"CUDA","level":2,"score":0.1834683120250702},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09489551186561584},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.08225741982460022},{"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/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"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":3,"locations":[{"id":"doi:10.1145/1851476.1851512","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1851476.1851512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:research.vu.nl:publications/7df58cce-29e1-49f6-a514-c20f1c84fd5d","is_oa":false,"landing_page_url":"https://hdl.handle.net/1871.1/7df58cce-29e1-49f6-a514-c20f1c84fd5d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401107","display_name":"VU Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I865915315","host_organization_name":"Vrije Universiteit Amsterdam","host_organization_lineage":["https://openalex.org/I865915315"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Liu, F & Seinstra, F J 2010, GPU-based Parallel Householder Bidiagonalization. in Proceedings of the 19th ACM International Symposium on High-Performance Distributed Computing (HPDC). Chicago, IL, USA.","raw_type":"contributionToPeriodical"},{"id":"pmh:vu:oai:research.vu.nl:publications/7df58cce-29e1-49f6-a514-c20f1c84fd5d","is_oa":false,"landing_page_url":"https://research.vu.nl/en/publications/7df58cce-29e1-49f6-a514-c20f1c84fd5d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the 19th ACM International Symposium on High-Performance Distributed Computing (HPDC)","raw_type":"info:eu-repo/semantics/conferencepaper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4608958112","display_name":null,"funder_award_id":"643.000.602","funder_id":"https://openalex.org/F4320321800","funder_display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek"}],"funders":[{"id":"https://openalex.org/F4320321800","display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","ror":"https://ror.org/04jsz6e67"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1511684433","https://openalex.org/W1979191869","https://openalex.org/W2078841894","https://openalex.org/W2132027201","https://openalex.org/W2136834900","https://openalex.org/W2155079435","https://openalex.org/W2169547644","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2030992542","https://openalex.org/W1988437637","https://openalex.org/W2898722594","https://openalex.org/W1977700955","https://openalex.org/W2344713096","https://openalex.org/W4388311419","https://openalex.org/W2113856999","https://openalex.org/W2125326641","https://openalex.org/W2023938924","https://openalex.org/W4318969829"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"discuss":[4],"the":[5,36,57,73,76,81,109],"GPU-based":[6],"implementation":[7],"and":[8,65],"optimization":[9],"of":[10,22,39,62,75,83,96,108],"Householder":[11],"bidiagonalization,":[12],"a":[13,94,100],"matrix":[14],"factorization":[15],"method":[16],"which":[17],"is":[18],"an":[19,29],"integral":[20],"part":[21],"full":[23],"Singular":[24],"Value":[25],"Decomposition":[26],"(SVD)":[27],"-":[28],"important":[30],"algorithm":[31],"for":[32],"many":[33],"problems":[34],"in":[35,90,104],"research":[37],"domain":[38],"Multimedia":[40],"Content":[41],"Analysis":[42],"(MMCA).":[43],"On":[44],"cluster":[45],"computers,":[46],"complex":[47,86],"adaptive":[48],"run-time":[49,87],"techniques":[50,89],"often":[51],"must":[52],"be":[53],"implemented":[54],"to":[55,66],"overcome":[56],"growing":[58],"negative":[59],"performance":[60,95],"impact":[61],"load":[63],"imbalances":[64],"ensure":[67],"reasonable":[68],"speedup.":[69],"We":[70],"show":[71],"that":[72],"nature":[74],"many-core":[77],"platform":[78],"can":[79],"avoid":[80],"necessity":[82],"applying":[84],"such":[85],"parallelization":[88],"software":[91],"while":[92],"achieving":[93],"64":[97],"gigaflops/s":[98],"on":[99],"single-GPU":[101],"GTX":[102],"295":[103],"double":[105],"precision,":[106],"82%":[107],"theoretical":[110],"peak":[111],"performance.":[112]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}