{"id":"https://openalex.org/W4409282772","doi":"https://doi.org/10.1145/3676536.3697131","title":"Error Correction and Detection for Analog AI Computing in Edge Systems","display_name":"Error Correction and Detection for Analog AI Computing in Edge Systems","publication_year":2024,"publication_date":"2024-10-27","ids":{"openalex":"https://openalex.org/W4409282772","doi":"https://doi.org/10.1145/3676536.3697131"},"language":"en","primary_location":{"id":"doi:10.1145/3676536.3697131","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3676536.3697131","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3676536.3697131","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3676536.3697131","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103150810","display_name":"Anxiao Jiang","orcid":"https://orcid.org/0000-0002-0120-7930"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Anxiao Jiang","raw_affiliation_strings":["Computer Science and Engineering, Texas A&M University, College Station, TX, United States"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, Texas A&M University, College Station, TX, United States","institution_ids":["https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5103150810"],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26736813,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9944999814033508,"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":0.9944999814033508,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9922000169754028,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.980400025844574,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6969923377037048},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5326383113861084},{"id":"https://openalex.org/keywords/error-detection-and-correction","display_name":"Error detection and correction","score":0.5046170949935913},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3878485858440399},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19677641987800598}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6969923377037048},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5326383113861084},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.5046170949935913},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3878485858440399},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19677641987800598}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3676536.3697131","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3676536.3697131","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3676536.3697131","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3676536.3697131","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3676536.3697131","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3676536.3697131","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4382876918","display_name":null,"funder_award_id":"2416361","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7432915178","display_name":null,"funder_award_id":"CCF-2416361","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","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/W4409282772.pdf","grobid_xml":"https://content.openalex.org/works/W4409282772.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W2014414302","https://openalex.org/W2027013453","https://openalex.org/W2030671441","https://openalex.org/W2083360820","https://openalex.org/W2096408325","https://openalex.org/W2111319461","https://openalex.org/W2116091101","https://openalex.org/W2121402134","https://openalex.org/W2140911008","https://openalex.org/W2149941495","https://openalex.org/W2169665116","https://openalex.org/W2603245559","https://openalex.org/W2890613163","https://openalex.org/W2962844766","https://openalex.org/W3003821665","https://openalex.org/W3009878528","https://openalex.org/W3013080934","https://openalex.org/W3024355533","https://openalex.org/W3103875393","https://openalex.org/W3112668161","https://openalex.org/W3139348684","https://openalex.org/W3165174904","https://openalex.org/W4252713891","https://openalex.org/W4310902900","https://openalex.org/W4313430026","https://openalex.org/W4385896568","https://openalex.org/W4386736788"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"To":[0],"realize":[1],"the":[2,27,39,53,65,97,110],"full":[3],"potential":[4],"of":[5,32,55,67,77,99,114,121],"deep":[6],"neural":[7],"networks":[8],"(DNNs)":[9],"in":[10,69,79,88],"AI-empowered":[11],"edge":[12,90],"systems,":[13],"DNNs":[14],"need":[15],"to":[16],"be":[17],"much":[18],"more":[19],"efficient.":[20],"Analog":[21],"in-memory":[22],"computing":[23],"can":[24],"potentially":[25],"improve":[26],"speed":[28],"and":[29,37,94],"energy":[30],"efficiency":[31],"AI":[33],"by":[34],"multiple":[35],"orders,":[36],"break":[38],"\"memory":[40],"wall\"":[41],"that":[42,108,125],"is":[43],"currently":[44],"a":[45,74,104,119],"major":[46],"bottleneck":[47],"for":[48],"AI.":[49],"This":[50],"work":[51],"explores":[52],"design":[54],"analog":[56,89],"error-correcting":[57],"codes":[58,62,82,124],"(Analog":[59],"ECCs).":[60],"The":[61,81],"focus":[63,95],"on":[64,96],"correction":[66,98],"errors":[68],"vector-matrix":[70],"multiplications,":[71],"which":[72],"are":[73],"dominant":[75],"part":[76],"computation":[78],"DNNs.":[80],"consider":[83],"small":[84],"but":[85],"ubiquitous":[86],"noise":[87],"circuits":[91],"as":[92],"tolerable,":[93],"large":[100],"errors.":[101],"It":[102,116],"presents":[103,118],"linear-programming":[105],"based":[106],"algorithm":[107],"finds":[109],"error":[111],"correction/detection":[112],"capabilities":[113],"codes.":[115],"also":[117],"number":[120],"newly":[122],"discovered":[123],"achieve":[126],"state-of-the-art":[127],"performance.":[128]},"counts_by_year":[],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}