{"id":"https://openalex.org/W2122221396","doi":"https://doi.org/10.1109/fpl.2009.5272262","title":"A highly scalable Restricted Boltzmann Machine FPGA implementation","display_name":"A highly scalable Restricted Boltzmann Machine FPGA implementation","publication_year":2009,"publication_date":"2009-08-01","ids":{"openalex":"https://openalex.org/W2122221396","doi":"https://doi.org/10.1109/fpl.2009.5272262","mag":"2122221396"},"language":"en","primary_location":{"id":"doi:10.1109/fpl.2009.5272262","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fpl.2009.5272262","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Conference on Field Programmable Logic and Applications","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/A5057447649","display_name":"Sang Gyune Kim","orcid":"https://orcid.org/0000-0001-8694-777X"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sang Kyun Kim","raw_affiliation_strings":["Department of Electrical Engineering, Stanford University, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027894657","display_name":"Lawrence McAfee","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lawrence C. McAfee","raw_affiliation_strings":["Department of Electrical Engineering, Stanford University, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064735957","display_name":"Peter L. McMahon","orcid":"https://orcid.org/0000-0002-1177-9887"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter L. McMahon","raw_affiliation_strings":["Department of Electrical Engineering, Stanford University, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023857198","display_name":"Kunle Olukotun","orcid":"https://orcid.org/0000-0002-8779-0636"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kunle Olukotun","raw_affiliation_strings":["Department of Electrical Engineering, Stanford University, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5057447649"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":2.9525,"has_fulltext":false,"cited_by_count":82,"citation_normalized_percentile":{"value":0.91949276,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"367","last_page":"372"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9970999956130981,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.996399998664856,"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/scalability","display_name":"Scalability","score":0.8015328645706177},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7897140979766846},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.7403898239135742},{"id":"https://openalex.org/keywords/boltzmann-machine","display_name":"Boltzmann machine","score":0.586253821849823},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4975924789905548},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.4131712019443512},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.40214836597442627},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.34669336676597595},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.18454810976982117},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1548294723033905},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.08640888333320618}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.8015328645706177},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7897140979766846},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.7403898239135742},{"id":"https://openalex.org/C192576344","wikidata":"https://www.wikidata.org/wiki/Q194706","display_name":"Boltzmann machine","level":3,"score":0.586253821849823},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4975924789905548},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.4131712019443512},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.40214836597442627},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.34669336676597595},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.18454810976982117},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1548294723033905},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.08640888333320618}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/fpl.2009.5272262","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fpl.2009.5272262","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Conference on Field Programmable Logic and Applications","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.220.1788","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.220.1788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ppl.stanford.edu/papers/fpl09_dbn.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1510973816","https://openalex.org/W1524093576","https://openalex.org/W1583056432","https://openalex.org/W1973695593","https://openalex.org/W1992286510","https://openalex.org/W2016415759","https://openalex.org/W2130017646","https://openalex.org/W2133257461","https://openalex.org/W2136922672","https://openalex.org/W2150609304","https://openalex.org/W2158164339","https://openalex.org/W6679718588"],"related_works":["https://openalex.org/W2364921833","https://openalex.org/W1604898313","https://openalex.org/W2385146268","https://openalex.org/W1596201972","https://openalex.org/W2095345650","https://openalex.org/W1788737569","https://openalex.org/W2503642292","https://openalex.org/W2320205417","https://openalex.org/W4308084229","https://openalex.org/W2468642654"],"abstract_inverted_index":{"Restricted":[0],"Boltzmann":[1],"machines":[2],"(RBMs)-":[3],"the":[4,34,53,63],"building":[5],"block":[6],"for":[7,20,91],"newly":[8],"popular":[9],"deep":[10],"belief":[11],"networks":[12],"(DBNs)":[13],"-":[14],"are":[15],"a":[16,45,59,67,82,123,136],"promising":[17],"new":[18],"tool":[19],"machine":[21,70],"learning":[22,71],"practitioners.":[23],"However,":[24],"future":[25],"research":[26],"in":[27,58],"applications":[28],"of":[29,55,65,125],"DBNs":[30],"is":[31,105],"hampered":[32],"by":[33],"considerable":[35],"computation":[36],"that":[37,51,69,100,122],"training":[38,54,94],"requires.":[39],"In":[40],"this":[41],"paper,":[42],"we":[43,108],"describe":[44],"novel":[46],"architecture":[47,86],"and":[48,107],"FPGA":[49],"implementation":[50,134],"accelerates":[52],"general":[56],"RBMs":[57],"scalable":[60],"manner,":[61],"with":[62],"goal":[64],"producing":[66],"system":[68],"researchers":[72],"can":[73,127],"use":[74,110],"to":[75,120],"investigate":[76],"ever-larger":[77],"networks.":[78],"Our":[79],"design":[80],"uses":[81],"highly":[83],"efficient,":[84],"fully-pipelined":[85],"based":[87],"on":[88,95,135],"16-bit":[89,102],"arithmetic":[90,103],"performing":[92],"RBM":[93],"an":[96,131],"FPGA.":[97],"We":[98,116],"show":[99,121],"only":[101],"precision":[104],"necessary,":[106],"consequently":[109],"embedded":[111],"hardware":[112],"multiply-and-add":[113],"(MADD)":[114],"units.":[115],"present":[117],"performance":[118],"results":[119],"speedup":[124],"25-30X":[126],"be":[128],"achieved":[129],"over":[130],"optimized":[132],"software":[133],"high-end":[137],"CPU.":[138]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":14},{"year":2015,"cited_by_count":11},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
