{"id":"https://openalex.org/W2625222559","doi":"https://doi.org/10.1145/3061639.3062307","title":"Real-Time Meets Approximate Computing","display_name":"Real-Time Meets Approximate Computing","publication_year":2017,"publication_date":"2017-06-13","ids":{"openalex":"https://openalex.org/W2625222559","doi":"https://doi.org/10.1145/3061639.3062307","mag":"2625222559"},"language":"en","primary_location":{"id":"doi:10.1145/3061639.3062307","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3061639.3062307","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 54th Annual Design Automation Conference 2017","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/A5100346965","display_name":"Ying Wang","orcid":"https://orcid.org/0000-0001-5172-4736"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ying Wang","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P.R. China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P.R. China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100768288","display_name":"Huawei Li","orcid":"https://orcid.org/0000-0001-8082-4218"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huawei Li","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P.R. China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P.R. China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023380073","display_name":"Xiaowei Li","orcid":"https://orcid.org/0000-0002-0874-814X"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowei Li","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P.R. China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, P.R. China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100346965"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"],"apc_list":null,"apc_paid":null,"fwci":1.8987,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.86670578,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9993000030517578,"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":0.8291918039321899},{"id":"https://openalex.org/keywords/hardware-acceleration","display_name":"Hardware acceleration","score":0.5948034524917603},{"id":"https://openalex.org/keywords/quality-of-service","display_name":"Quality of service","score":0.5488484501838684},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.5356169939041138},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.5116482377052307},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4854336380958557},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4746024012565613},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4701445400714874},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4615945816040039},{"id":"https://openalex.org/keywords/control-reconfiguration","display_name":"Control reconfiguration","score":0.45143961906433105},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.44513165950775146},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.4295520782470703},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4130197763442993},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3217694163322449},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.20153498649597168},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13496050238609314}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8291918039321899},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.5948034524917603},{"id":"https://openalex.org/C5119721","wikidata":"https://www.wikidata.org/wiki/Q220501","display_name":"Quality of service","level":2,"score":0.5488484501838684},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.5356169939041138},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.5116482377052307},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4854336380958557},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4746024012565613},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4701445400714874},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4615945816040039},{"id":"https://openalex.org/C119701452","wikidata":"https://www.wikidata.org/wiki/Q5165881","display_name":"Control reconfiguration","level":2,"score":0.45143961906433105},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.44513165950775146},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.4295520782470703},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4130197763442993},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3217694163322449},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.20153498649597168},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13496050238609314},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3061639.3062307","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3061639.3062307","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 54th Annual Design Automation Conference 2017","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8899999856948853}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2003957094","https://openalex.org/W2117539524","https://openalex.org/W2119144962","https://openalex.org/W2152839228","https://openalex.org/W2187230075","https://openalex.org/W2403646140","https://openalex.org/W2554131156","https://openalex.org/W2618530766","https://openalex.org/W2963173190","https://openalex.org/W2964299589","https://openalex.org/W3147600416"],"related_works":["https://openalex.org/W2357657342","https://openalex.org/W2153432761","https://openalex.org/W1580144672","https://openalex.org/W2294545068","https://openalex.org/W4319952061","https://openalex.org/W4280636456","https://openalex.org/W4388913998","https://openalex.org/W4310584535","https://openalex.org/W4295935044","https://openalex.org/W3159906349"],"abstract_inverted_index":{"Due":[0],"to":[1,24,44,116,146,182],"the":[2,53,117,123,131,134,148,161,175,179,197,202],"recent":[3],"progress":[4],"in":[5,73,125,164,172,185],"deep":[6,13,64],"learning":[7,65],"and":[8,34,59,98,141,153,166,195],"neural":[9,14,18],"acceleration":[10,111],"architectures,":[11],"specialized":[12],"network":[15,19,138],"or":[16],"convolutional":[17],"(CNNs)":[20],"accelerators":[21,67,86],"are":[22,159],"expected":[23],"provide":[25],"an":[26,108,186],"energy-efficient":[27],"solution":[28],"for":[29],"real-time":[30,78,95,165,193],"vision/speech":[31],"processing.":[32,79],"recognition":[33],"a":[35,88],"wide":[36,46],"spectrum":[37],"of":[38,56,91,151,155,199],"approximate":[39,127,167],"computing":[40,128],"applications.":[41],"In":[42],"addition":[43],"their":[45],"applicability":[47],"scope,":[48],"we":[49],"also":[50],"found":[51],"that":[52,113,174],"fascinating":[54],"feature":[55],"deterministic":[57],"performance":[58],"high":[60],"energy-efficiency,":[61],"makes":[62],"such":[63],"(DL)":[66],"ideal":[68],"candidates":[69],"as":[70],"application-processor":[71],"IPs":[72],"embedded":[74,103,180],"SoCs":[75],"concerned":[76],"with":[77],"However,":[80],"unlike":[81],"traditional":[82],"accelerator":[83,143],"designs,":[84],"DL":[85],"introduce":[87],"new":[89],"aspect":[90],"design":[92,149],"trade-off":[93],"between":[94],"processing":[96],"(QoS)":[97],"computation":[99],"approximation":[100],"(QoR)":[101],"into":[102],"systems.":[104],"This":[105],"work":[106,183],"proposes":[107],"elastic":[109],"CNN":[110],"architecture":[112,177],"automatically":[114],"adapts":[115],"hard":[118],"QoS":[119,152],"constraint":[120,150,205],"by":[121],"exploiting":[122],"error-resilience":[124],"typical":[126],"workloads":[129],"For":[130],"first":[132],"time,":[133],"proposed":[135,176],"design,":[136],"including":[137],"tuning-and-mapping":[139],"software":[140],"reconfigurable":[142],"hardware,":[144],"aims":[145],"reconcile":[147],"Quality":[154],"Result":[156],"(QoR).":[157],"which":[158],"respectively":[160],"key":[162],"concerns":[163],"computing.":[168],"It":[169],"is":[170],"shown":[171],"experiments":[173],"enables":[178],"system":[181,200],"flexibly":[184],"expanded":[187],"operating":[188],"space,":[189],"significantly":[190],"enhances":[191],"its":[192],"ability.":[194],"maximizes":[196],"energy-efficiency":[198],"within":[201],"user-specified":[203],"QoS-QoR":[204],"through":[206],"self-reconfiguration.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}