{"id":"https://openalex.org/W2406576396","doi":"https://doi.org/10.1109/vts.2016.7477304","title":"SRAM yield-per-area optimization under spatially-correlated process variation","display_name":"SRAM yield-per-area optimization under spatially-correlated process variation","publication_year":2016,"publication_date":"2016-04-01","ids":{"openalex":"https://openalex.org/W2406576396","doi":"https://doi.org/10.1109/vts.2016.7477304","mag":"2406576396"},"language":"en","primary_location":{"id":"doi:10.1109/vts.2016.7477304","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vts.2016.7477304","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 34th VLSI Test Symposium (VTS)","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/A5102781111","display_name":"Jizhe Zhang","orcid":"https://orcid.org/0000-0003-2032-3598"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jizhe Zhang","raw_affiliation_strings":["Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100601790","display_name":"Sandeep K. Gupta","orcid":"https://orcid.org/0000-0002-2585-9378"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sandeep K. Gupta","raw_affiliation_strings":["Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03871497,"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":"6"},"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/T11522","display_name":"VLSI and FPGA Design Techniques","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/T11032","display_name":"VLSI and Analog Circuit Testing","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"}}],"keywords":[{"id":"https://openalex.org/keywords/static-random-access-memory","display_name":"Static random-access memory","score":0.8881220817565918},{"id":"https://openalex.org/keywords/process-variation","display_name":"Process variation","score":0.7748024463653564},{"id":"https://openalex.org/keywords/spare-part","display_name":"Spare part","score":0.6846989989280701},{"id":"https://openalex.org/keywords/variation","display_name":"Variation (astronomy)","score":0.6343758702278137},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.6322456002235413},{"id":"https://openalex.org/keywords/row","display_name":"Row","score":0.6217073202133179},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6157563924789429},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6127234101295471},{"id":"https://openalex.org/keywords/row-and-column-spaces","display_name":"Row and column spaces","score":0.5904194712638855},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48445701599121094},{"id":"https://openalex.org/keywords/transistor","display_name":"Transistor","score":0.43570244312286377},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1793263852596283},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.16996994614601135},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16000527143478394},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.1566987931728363},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06674101948738098}],"concepts":[{"id":"https://openalex.org/C68043766","wikidata":"https://www.wikidata.org/wiki/Q267416","display_name":"Static random-access memory","level":2,"score":0.8881220817565918},{"id":"https://openalex.org/C93389723","wikidata":"https://www.wikidata.org/wiki/Q7247313","display_name":"Process variation","level":3,"score":0.7748024463653564},{"id":"https://openalex.org/C194648553","wikidata":"https://www.wikidata.org/wiki/Q1364774","display_name":"Spare part","level":2,"score":0.6846989989280701},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.6343758702278137},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.6322456002235413},{"id":"https://openalex.org/C135598885","wikidata":"https://www.wikidata.org/wiki/Q1366302","display_name":"Row","level":2,"score":0.6217073202133179},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6157563924789429},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6127234101295471},{"id":"https://openalex.org/C104140500","wikidata":"https://www.wikidata.org/wiki/Q2088159","display_name":"Row and column spaces","level":3,"score":0.5904194712638855},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48445701599121094},{"id":"https://openalex.org/C172385210","wikidata":"https://www.wikidata.org/wiki/Q5339","display_name":"Transistor","level":3,"score":0.43570244312286377},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1793263852596283},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.16996994614601135},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16000527143478394},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.1566987931728363},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06674101948738098},{"id":"https://openalex.org/C44870925","wikidata":"https://www.wikidata.org/wiki/Q37547","display_name":"Astrophysics","level":1,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vts.2016.7477304","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vts.2016.7477304","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 34th VLSI Test Symposium (VTS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1693570377","https://openalex.org/W1995280594","https://openalex.org/W2001881266","https://openalex.org/W2015620003","https://openalex.org/W2018632396","https://openalex.org/W2064187704","https://openalex.org/W2069345435","https://openalex.org/W2073217565","https://openalex.org/W2075123181","https://openalex.org/W2118749577","https://openalex.org/W2120353978","https://openalex.org/W2132621842","https://openalex.org/W2149606298","https://openalex.org/W2150283124","https://openalex.org/W2154477062","https://openalex.org/W2155640457","https://openalex.org/W2464177207","https://openalex.org/W3146563601","https://openalex.org/W4205474030","https://openalex.org/W4243073678","https://openalex.org/W6677720047","https://openalex.org/W6678361433"],"related_works":["https://openalex.org/W2313440505","https://openalex.org/W3123744736","https://openalex.org/W2137691148","https://openalex.org/W1505848319","https://openalex.org/W2905020035","https://openalex.org/W4281399881","https://openalex.org/W2433052208","https://openalex.org/W3166006430","https://openalex.org/W4281971614","https://openalex.org/W2096502566"],"abstract_inverted_index":{"Spatial":[0],"correlation":[1,20],"of":[2,18,47,66,82],"process":[3,53,87],"variation":[4,13,54],"increases":[5],"the":[6,16,45,56,64,92,97],"probability":[7],"that":[8,44,91],"nearby":[9],"transistors":[10],"have":[11],"similar":[12],"values.":[14],"However,":[15],"impact":[17],"spatial":[19],"on":[21],"yield":[22,59],"enhancement":[23],"techniques,":[24],"such":[25],"as":[26],"spare":[27,67],"rows":[28,68],"and":[29,69],"columns":[30],"for":[31],"SRAM":[32,57,83],"arrays,":[33],"has":[34],"not":[35],"been":[36],"well":[37],"understood.":[38],"In":[39],"this":[40],"paper":[41],"we":[42],"find":[43],"clustering":[46],"failing":[48],"cells":[49],"caused":[50],"by":[51],"spatially-correlated":[52],"makes":[55],"array":[58],"much":[60],"less":[61],"sensitive":[62],"to":[63,78],"number":[65],"columns.":[70],"We":[71,89],"then":[72],"propose":[73],"a":[74],"coarse-to-fine":[75],"search":[76],"method":[77,94],"optimize":[79],"yield-per-area":[80],"(YPA)":[81],"systems":[84],"under":[85],"correlated":[86],"variation.":[88],"show":[90],"proposed":[93],"can":[95],"identify":[96],"optimal":[98],"design":[99],"efficiently.":[100]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}