{"id":"https://openalex.org/W2087214224","doi":"https://doi.org/10.1109/asap.2013.6567549","title":"Accelerating HAC estimation for multivariate time series","display_name":"Accelerating HAC estimation for multivariate time series","publication_year":2013,"publication_date":"2013-06-01","ids":{"openalex":"https://openalex.org/W2087214224","doi":"https://doi.org/10.1109/asap.2013.6567549","mag":"2087214224"},"language":"en","primary_location":{"id":"doi:10.1109/asap.2013.6567549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asap.2013.6567549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE 24th International Conference on Application-Specific Systems, Architectures and Processors","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://zenodo.org/record/3429986","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083303676","display_name":"Ce Guo","orcid":"https://orcid.org/0000-0002-0272-9175"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Ce Guo","raw_affiliation_strings":["Department of Computing, Imperial College, London, UK","Dept. of Comput., Imperial Coll. London, London, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computing, Imperial College, London, UK","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Dept. of Comput., Imperial Coll. London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057940557","display_name":"Wayne Luk","orcid":"https://orcid.org/0000-0002-6750-927X"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Wayne Luk","raw_affiliation_strings":["Department of Computing, Imperial College, London, UK","Dept. of Comput., Imperial Coll. London, London, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computing, Imperial College, London, UK","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Dept. of Comput., Imperial Coll. London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5083303676"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":1.4427,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.86098369,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"55","issue":null,"first_page":"42","last_page":"49"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9951000213623047,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9951000213623047,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9944999814033508,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7413946986198425},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5927844643592834},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.5843513011932373},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5790724158287048},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4967944920063019},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.4816495478153229},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.46909770369529724},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46137723326683044},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.44665947556495667},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.4347561001777649},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.4279567301273346},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.41982191801071167},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.17513170838356018},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14602014422416687},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12496086955070496},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11478227376937866}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7413946986198425},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5927844643592834},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.5843513011932373},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5790724158287048},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4967944920063019},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.4816495478153229},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.46909770369529724},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46137723326683044},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.44665947556495667},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.4347561001777649},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.4279567301273346},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.41982191801071167},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.17513170838356018},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14602014422416687},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12496086955070496},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11478227376937866},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/asap.2013.6567549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asap.2013.6567549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE 24th International Conference on Application-Specific Systems, Architectures and Processors","raw_type":"proceedings-article"},{"id":"pmh:oai:zenodo.org:3429986","is_oa":true,"landing_page_url":"https://zenodo.org/record/3429986","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferencePaper"}],"best_oa_location":{"id":"pmh:oai:zenodo.org:3429986","is_oa":true,"landing_page_url":"https://zenodo.org/record/3429986","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferencePaper"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1484413656","https://openalex.org/W1995670019","https://openalex.org/W2044503966","https://openalex.org/W2047682070","https://openalex.org/W2065180335","https://openalex.org/W2068686165","https://openalex.org/W2097335492","https://openalex.org/W2100327879","https://openalex.org/W2108446661","https://openalex.org/W2111354851","https://openalex.org/W2112683038","https://openalex.org/W2117178635","https://openalex.org/W2125520394","https://openalex.org/W2127218421","https://openalex.org/W2133645803","https://openalex.org/W2136362180","https://openalex.org/W2141185104","https://openalex.org/W2143193290","https://openalex.org/W2149706766","https://openalex.org/W2152142354","https://openalex.org/W2161831889","https://openalex.org/W3021107451","https://openalex.org/W3023906401","https://openalex.org/W3123737450","https://openalex.org/W3124550551","https://openalex.org/W3146166473","https://openalex.org/W4236137412","https://openalex.org/W4240639369","https://openalex.org/W4241115065","https://openalex.org/W4248283403","https://openalex.org/W6628750762","https://openalex.org/W6678914141","https://openalex.org/W6680518677"],"related_works":["https://openalex.org/W747394405","https://openalex.org/W1987236514","https://openalex.org/W174653542","https://openalex.org/W2381153750","https://openalex.org/W2041235277","https://openalex.org/W2088220880","https://openalex.org/W2022021973","https://openalex.org/W2886934452","https://openalex.org/W1489099099","https://openalex.org/W2024369332"],"abstract_inverted_index":{"Heteroskedasticity":[0],"and":[1,24,36,44,74,100,105,133],"autocorrelation":[2],"consistent":[3],"(HAC)":[4],"covariance":[5],"matrix":[6],"estimation,":[7],"or":[8],"HAC":[9,40,57],"estimation":[10,41,58],"in":[11,20,79],"short,":[12],"is":[13,48,95,119],"one":[14,131],"of":[15,115],"the":[16,90,116],"most":[17],"important":[18],"techniques":[19],"time":[21,46],"series":[22,47],"analysis":[23],"forecasting.":[25],"It":[26],"serves":[27],"as":[28],"a":[29,54,62,84,138],"powerful":[30],"analytical":[31],"tool":[32],"for":[33,42],"hypothesis":[34],"testing":[35],"model":[37],"verification.":[38],"However,":[39],"long":[43],"high-dimensional":[45],"computationally":[49],"expensive.":[50],"This":[51,93],"paper":[52],"describes":[53],"novel":[55],"pipeline-friendly":[56],"algorithm":[59],"derived":[60],"from":[61,102],"mathematical":[63],"specification,":[64],"by":[65],"applying":[66],"transformations":[67],"to":[68,71,75,97,121],"eliminate":[69],"conditionals,":[70],"parallelize":[72],"arithmetic,":[73],"promote":[76],"data":[77],"reuse":[78],"computation.":[80],"We":[81],"then":[82],"develop":[83],"fully-pipelined":[85],"hardware":[86],"architecture":[87,94,118],"based":[88],"on":[89],"proposed":[91,117],"algorithm.":[92],"shown":[96],"be":[98],"efficient":[99],"scalable":[101],"both":[103],"theoretical":[104],"empirical":[106],"perspectives.":[107],"Experimental":[108],"results":[109],"show":[110],"that":[111],"an":[112,126],"FPGA-based":[113],"implementation":[114,129],"up":[120],"111":[122],"times":[123,135],"faster":[124,136],"than":[125,137],"optimised":[127],"CPU":[128,139],"with":[130,140],"core,":[132],"14":[134],"eight":[141],"cores.":[142]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}
