{"id":"https://openalex.org/W2392474488","doi":"https://doi.org/10.1145/2902961.2902986","title":"Low-Power Manycore Accelerator for Personalized Biomedical Applications","display_name":"Low-Power Manycore Accelerator for Personalized Biomedical Applications","publication_year":2016,"publication_date":"2016-05-13","ids":{"openalex":"https://openalex.org/W2392474488","doi":"https://doi.org/10.1145/2902961.2902986","mag":"2392474488"},"language":"en","primary_location":{"id":"doi:10.1145/2902961.2902986","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2902961.2902986","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2902986&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th edition on Great Lakes Symposium on VLSI","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://dl.acm.org/ft_gateway.cfm?id=2902986&type=pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083141354","display_name":"Adam Page","orcid":"https://orcid.org/0000-0001-8220-2594"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Adam Page","raw_affiliation_strings":["University of Maryland, Baltimore County, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, Baltimore County, Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032609374","display_name":"Nasrin Attaran","orcid":"https://orcid.org/0000-0003-2513-2213"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nasrin Attaran","raw_affiliation_strings":["University of Maryland, Baltimore County, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, Baltimore County, Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022091861","display_name":"Colin Shea","orcid":"https://orcid.org/0000-0002-3269-5244"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Colin Shea","raw_affiliation_strings":["University of Maryland, Baltimore County, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, Baltimore County, Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047382437","display_name":"Houman Homayoun","orcid":"https://orcid.org/0000-0001-8904-4699"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Houman Homayoun","raw_affiliation_strings":["George Mason University, Fairfax, VA, USA"],"affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084010501","display_name":"Tinoosh Mohsenin","orcid":"https://orcid.org/0000-0001-5551-2124"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tinoosh Mohsenin","raw_affiliation_strings":["University of Maryland, Baltimore County, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, Baltimore County, Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5083141354"],"corresponding_institution_ids":["https://openalex.org/I79272384"],"apc_list":null,"apc_paid":null,"fwci":2.5727,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.90136647,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"63","last_page":"68"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10363","display_name":"Low-power high-performance VLSI design","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8158214092254639},{"id":"https://openalex.org/keywords/coprocessor","display_name":"Coprocessor","score":0.6412992477416992},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.568875253200531},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.5576095581054688},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.5503538846969604},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.5144227147102356},{"id":"https://openalex.org/keywords/wearable-technology","display_name":"Wearable technology","score":0.4830261170864105},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4504394233226776},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4439876675605774},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.4100058674812317},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.35860157012939453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28932976722717285}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8158214092254639},{"id":"https://openalex.org/C86111242","wikidata":"https://www.wikidata.org/wiki/Q859595","display_name":"Coprocessor","level":2,"score":0.6412992477416992},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.568875253200531},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.5576095581054688},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.5503538846969604},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.5144227147102356},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.4830261170864105},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4504394233226776},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4439876675605774},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.4100058674812317},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.35860157012939453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28932976722717285},{"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":1,"locations":[{"id":"doi:10.1145/2902961.2902986","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2902961.2902986","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2902986&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th edition on Great Lakes Symposium on VLSI","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/2902961.2902986","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2902961.2902986","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2902986&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th edition on Great Lakes Symposium on VLSI","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G2781130797","display_name":null,"funder_award_id":"00008999, 00010145","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2392474488.pdf","grobid_xml":"https://content.openalex.org/works/W2392474488.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W2003368250","https://openalex.org/W2037521271","https://openalex.org/W2040990639","https://openalex.org/W2042682017","https://openalex.org/W2044479847","https://openalex.org/W2047049615","https://openalex.org/W2047200429","https://openalex.org/W2058092201","https://openalex.org/W2086659790","https://openalex.org/W2101251534","https://openalex.org/W2110653637","https://openalex.org/W2188648459","https://openalex.org/W2199987002","https://openalex.org/W2296399887","https://openalex.org/W2442112158","https://openalex.org/W2511296762","https://openalex.org/W2517777200","https://openalex.org/W4229976825"],"related_works":["https://openalex.org/W3090300519","https://openalex.org/W2514492205","https://openalex.org/W4250401876","https://openalex.org/W2943851981","https://openalex.org/W2566526749","https://openalex.org/W2907667791","https://openalex.org/W3047461507","https://openalex.org/W3126390843","https://openalex.org/W4245880644","https://openalex.org/W4210376836"],"abstract_inverted_index":{"Wearable":[0],"personal":[1],"health":[2],"monitoring":[3],"systems":[4,15],"can":[5],"offer":[6],"a":[7,90,109,169],"cost":[8],"effective":[9],"solution":[10],"for":[11,149],"human":[12],"healthcare.":[13],"These":[14,58],"must":[16,48],"provide":[17],"both":[18],"highly":[19],"accurate,":[20],"secured":[21],"and":[22,25,42,54,63,73,85,97,124,147,151,191],"quick":[23],"processing":[24,64,77,96,183,219],"delivery":[26],"of":[27,30,67,80,93,128,161],"vast":[28],"amount":[29],"data.":[31],"In":[32,101],"addition,":[33],"wearable":[34],"biomedical":[35,53,59],"devices":[36],"are":[37],"used":[38],"in":[39,106],"inpatient,":[40],"outpatient,":[41],"at":[43],"home":[44],"e-Patient":[45],"care":[46],"that":[47,88,134,201],"constantly":[49],"monitor":[50],"the":[51,126,135,162,202,207],"patient's":[52],"physiological":[55,68],"signals":[56,69],"24/7.":[57],"applications":[60],"require":[61,89],"sampling":[62],"multiple":[65],"streams":[66],"with":[70,178,195],"strict":[71],"power":[72],"area":[74],"footprint.":[75],"The":[76,159,198],"typically":[78],"consists":[79],"feature":[81],"extraction,":[82],"data":[83],"fusion,":[84],"classification":[86],"stages":[87],"large":[91],"number":[92],"digital":[94],"signal":[95],"machine":[98,152,224],"learning":[99,153,225],"kernels.":[100],"response":[102],"to":[103,122,139,145,171],"these":[104,129],"requirements,":[105],"this":[107],"paper,":[108],"low-power,":[110],"domain-specific":[111],"many-core":[112],"accelerator":[113],"named":[114],"Power":[115],"Efficient":[116],"Nano":[117],"Clusters":[118],"(PENC)":[119],"is":[120,137,176],"proposed":[121,163],"map":[123],"execute":[125],"kernels":[127],"applications.":[130],"Experimental":[131],"results":[132,199],"show":[133,200],"manycore":[136,165,204],"able":[138],"reduce":[140],"energy":[141,208],"consumption":[142],"by":[143,209],"up":[144],"80%":[146],"14%":[148],"DSP":[150],"kernels,":[154],"respectively,":[155],"when":[156,166],"optimally":[157],"parallelized.":[158],"performance":[160],"PENC":[164,203],"acting":[167],"as":[168,210,212],"coprocessor":[170],"an":[172],"Intel":[173,186],"Atom":[174],"processor":[175],"compared":[177],"existing":[179],"commercial":[180],"off-the-shelf":[181,217],"embedded":[182,218],"platforms":[184,220],"including":[185],"Atom,":[187],"Xilinx":[188],"Artix-7":[189],"FPGA,":[190],"NVIDIA":[192],"TK1":[193],"ARM-A15":[194],"GPU":[196],"SoC.":[197],"architecture":[205],"reduces":[206],"much":[211],"10X":[213],"while":[214],"outperforming":[215],"all":[216,222],"across":[221],"studied":[223],"classifiers.":[226]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
