{"id":"https://openalex.org/W2905996924","doi":"https://doi.org/10.1109/tvlsi.2018.2884848","title":"Toward Self-Tunable Approximate Computing","display_name":"Toward Self-Tunable Approximate Computing","publication_year":2018,"publication_date":"2018-12-20","ids":{"openalex":"https://openalex.org/W2905996924","doi":"https://doi.org/10.1109/tvlsi.2018.2884848","mag":"2905996924"},"language":"en","primary_location":{"id":"doi:10.1109/tvlsi.2018.2884848","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvlsi.2018.2884848","pdf_url":null,"source":{"id":"https://openalex.org/S37538908","display_name":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","issn_l":"1063-8210","issn":["1063-8210","1557-9999"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","raw_type":"journal-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/A5101819650","display_name":"Siyuan Xu","orcid":"https://orcid.org/0000-0001-6239-6774"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siyuan Xu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX, USA"],"raw_orcid":"https://orcid.org/0000-0001-6239-6774","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064356970","display_name":"Benjamin Carri\u00f3n Sch\u00e4fer","orcid":"https://orcid.org/0000-0002-4755-6503"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Benjamin Carrion Schafer","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162577319"],"apc_list":null,"apc_paid":null,"fwci":1.515,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.84069065,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"27","issue":"4","first_page":"778","last_page":"789"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10363","display_name":"Low-power high-performance VLSI design","score":0.9998999834060669,"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/T10363","display_name":"Low-power high-performance VLSI design","score":0.9998999834060669,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T11005","display_name":"Radiation Effects in Electronics","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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5326715707778931},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.39848577976226807}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5326715707778931},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.39848577976226807}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvlsi.2018.2884848","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvlsi.2018.2884848","pdf_url":null,"source":{"id":"https://openalex.org/S37538908","display_name":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","issn_l":"1063-8210","issn":["1063-8210","1557-9999"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W634728970","https://openalex.org/W1533950919","https://openalex.org/W1856540154","https://openalex.org/W1986192284","https://openalex.org/W1998824039","https://openalex.org/W2010966003","https://openalex.org/W2020217519","https://openalex.org/W2030922317","https://openalex.org/W2034270503","https://openalex.org/W2035378788","https://openalex.org/W2044235194","https://openalex.org/W2076536455","https://openalex.org/W2077212538","https://openalex.org/W2107376597","https://openalex.org/W2111444234","https://openalex.org/W2113592437","https://openalex.org/W2121662690","https://openalex.org/W2140145164","https://openalex.org/W2142883190","https://openalex.org/W2143556363","https://openalex.org/W2187230075","https://openalex.org/W2244005500","https://openalex.org/W2244803248","https://openalex.org/W2253595223","https://openalex.org/W2265166184","https://openalex.org/W2293636967","https://openalex.org/W2399535694","https://openalex.org/W2404305894","https://openalex.org/W2405102949","https://openalex.org/W2466529450","https://openalex.org/W2499900168","https://openalex.org/W2509971597","https://openalex.org/W2588565458","https://openalex.org/W2742536119","https://openalex.org/W2746351350","https://openalex.org/W2768781341","https://openalex.org/W2770370002","https://openalex.org/W2798414599","https://openalex.org/W2884390179","https://openalex.org/W3005460357","https://openalex.org/W4231563577","https://openalex.org/W4234974086","https://openalex.org/W4243410967","https://openalex.org/W4247431052","https://openalex.org/W6669791407","https://openalex.org/W6680702329"],"related_works":["https://openalex.org/W1604898313","https://openalex.org/W2117014006","https://openalex.org/W4233815414","https://openalex.org/W2372170743","https://openalex.org/W1491899005","https://openalex.org/W1558545464","https://openalex.org/W2172791042","https://openalex.org/W2074301136","https://openalex.org/W1502414128","https://openalex.org/W1984303163"],"abstract_inverted_index":{"Many":[0],"applications":[1],"show":[2,152],"tolerance":[3],"to":[4,10,82,160,165],"inaccuracies.":[5],"These":[6,138],"can":[7],"be":[8],"exploited":[9],"build":[11],"faster":[12],"circuits":[13,125],"with":[14,35],"smaller":[15],"area":[16],"and":[17,129,146,187,191,195,199],"lower":[18],"power.":[19],"This":[20],"is":[21,38,44,62],"particularly":[22],"true":[23],"for":[24,189],"the":[25,40,48,60,106,123,130,144,148,171,175],"hardware":[26],"accelerators":[27],"in":[28,64,90,143],"heterogeneous":[29],"computing":[30,37],"systems.":[31],"A":[32],"major":[33],"problem":[34],"approximate":[36,96,124],"that":[39,99,153],"resulting":[41],"approximated":[42],"circuit":[43],"highly":[45],"dependent":[46],"on":[47,55,105,116,133,184],"training":[49,57],"data.":[50],"Previous":[51],"works":[52],"often":[53],"rely":[54],"static":[56],"results.":[58],"If":[59],"workload":[61,145],"dynamic":[63,77],"nature":[65],"or":[66],"changes":[67],"over":[68],"time,":[69],"output":[70,172],"errors":[71],"may":[72],"reach":[73],"unacceptable":[74],"levels.":[75],"Therefore,":[76],"control":[78,110],"methods":[79,156,168],"are":[80,112],"needed":[81],"solve":[83],"this":[84,88,91],"problem.":[85],"To":[86],"address":[87],"issue,":[89],"paper,":[92],"we":[93],"propose":[94],"an":[95],"self-adaptive":[97],"architecture":[98],"autotunes":[100],"itself":[101],"at":[102,126,180],"runtime":[103],"based":[104,115,132],"workload.":[107],"Two":[108],"different":[109],"mechanisms":[111],"proposed,":[113],"one":[114],"a":[117,141],"regular":[118,127],"heartbeat":[119],"(HB),":[120],"which":[121],"resets":[122],"intervals":[128],"other":[131,166],"internal":[134],"lightweight":[135],"checkers":[136,139],"(LWCs).":[137],"detect":[140],"change":[142],"reset":[147],"approximations.":[149],"Experimental":[150],"results":[151,163],"our":[154],"proposed":[155],"work":[157],"well":[158],"leading":[159],"very":[161],"good":[162],"compared":[164],"approximation":[167],"while":[169],"keeping":[170],"error":[173,178],"within":[174],"given":[176],"maximum":[177],"threshold":[179],"relatively":[181],"low-area":[182],"overheads,":[183],"average":[185],"8%":[186],"8.5%":[188],"HB":[190],"LWC":[192],"method,":[193],"respectively,":[194],"delay":[196],"overheads":[197],"5.9%":[198],"8.1%.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
