{"id":"https://openalex.org/W2786708967","doi":"https://doi.org/10.1109/icm.2017.8268827","title":"Hardware accelerators for the K-nearest neighbor algorithm using high level synthesis","display_name":"Hardware accelerators for the K-nearest neighbor algorithm using high level synthesis","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2786708967","doi":"https://doi.org/10.1109/icm.2017.8268827","mag":"2786708967"},"language":"en","primary_location":{"id":"doi:10.1109/icm.2017.8268827","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icm.2017.8268827","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 29th International Conference on Microelectronics (ICM)","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/A5011322154","display_name":"Dunia Jamma","orcid":null},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Dunia Jamma","raw_affiliation_strings":["School of Engineering, University of Guelph, Guelph, Canada"],"affiliations":[{"raw_affiliation_string":"School of Engineering, University of Guelph, Guelph, Canada","institution_ids":["https://openalex.org/I79817857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047989984","display_name":"Omar Ahmed","orcid":"https://orcid.org/0000-0001-9880-838X"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Omar Ahmed","raw_affiliation_strings":["School of Engineering, University of Guelph, Guelph, Canada"],"affiliations":[{"raw_affiliation_string":"School of Engineering, University of Guelph, Guelph, Canada","institution_ids":["https://openalex.org/I79817857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011873620","display_name":"Shawki Areibi","orcid":"https://orcid.org/0000-0003-4832-0911"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Shawki Areibi","raw_affiliation_strings":["School of Engineering, University of Guelph, Guelph, Canada"],"affiliations":[{"raw_affiliation_string":"School of Engineering, University of Guelph, Guelph, Canada","institution_ids":["https://openalex.org/I79817857"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068888605","display_name":"Gary Gr\u00e9wal","orcid":"https://orcid.org/0000-0003-0845-6929"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Gary Grewal","raw_affiliation_strings":["School of Computer Science, University of Guelph, Guelph, Canada"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Guelph, Guelph, Canada","institution_ids":["https://openalex.org/I79817857"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5011322154"],"corresponding_institution_ids":["https://openalex.org/I79817857"],"apc_list":null,"apc_paid":null,"fwci":0.195,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.65111933,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9976000189781189,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9976000189781189,"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/T10320","display_name":"Neural Networks and Applications","score":0.9884999990463257,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9825000166893005,"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/computer-science","display_name":"Computer science","score":0.8062670230865479},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.7289654016494751},{"id":"https://openalex.org/keywords/high-level-synthesis","display_name":"High-level synthesis","score":0.5826389789581299},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.5425610542297363},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5365735292434692},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.432100385427475},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.39924517273902893},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27824798226356506},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.18370670080184937}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8062670230865479},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.7289654016494751},{"id":"https://openalex.org/C58013763","wikidata":"https://www.wikidata.org/wiki/Q5754574","display_name":"High-level synthesis","level":3,"score":0.5826389789581299},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.5425610542297363},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5365735292434692},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.432100385427475},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.39924517273902893},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27824798226356506},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.18370670080184937},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icm.2017.8268827","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icm.2017.8268827","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 29th International Conference on Microelectronics (ICM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1873332500","https://openalex.org/W2006343380","https://openalex.org/W2063459162","https://openalex.org/W2096328040","https://openalex.org/W2518935935","https://openalex.org/W3120740533","https://openalex.org/W6639175750"],"related_works":["https://openalex.org/W2783354812","https://openalex.org/W4384112194","https://openalex.org/W2103009189","https://openalex.org/W4312958259","https://openalex.org/W4308259661","https://openalex.org/W4390813131","https://openalex.org/W2349383066","https://openalex.org/W4328132048","https://openalex.org/W2612099726","https://openalex.org/W2160632767"],"abstract_inverted_index":{"Supervised":[0],"machine-learning":[1],"algorithms":[2],"require":[3],"relatively":[4],"large":[5],"amounts":[6],"of":[7,56],"runtime":[8],"to":[9,18],"perform":[10],"training":[11],"and/or":[12],"classification.":[13],"Therefore,":[14],"a":[15],"need":[16],"exists":[17],"accelerate":[19],"their":[20],"runtime,":[21],"especially":[22],"for":[23,36],"real-time":[24],"applications.":[25],"In":[26],"this":[27],"paper,":[28],"we":[29],"propose":[30],"and":[31,53],"compare":[32],"several":[33],"hardware":[34],"accelerators":[35,44],"the":[37],"K-Nearest":[38],"Neighbor":[39],"(K-NN)":[40],"classification":[41],"algorithm.":[42],"The":[43],"are":[45],"developed":[46],"using":[47],"Xilinx":[48],"Vivado":[49],"High-Level":[50],"Synthesis":[51],"(HLS)":[52],"represent":[54],"examples":[55],"semi-tightly":[57],"coupled":[58],"architectures.":[59],"Our":[60],"experimental":[61],"results,":[62],"based":[63],"on":[64],"standard":[65],"benchmarks,":[66],"show":[67],"speedups":[68],"ranging":[69],"from":[70],"48x-168x.":[71]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
