{"id":"https://openalex.org/W7123568625","doi":"https://doi.org/10.1145/3772052.3772234","title":"DRAM Failure Prediction with Correctable Error Spatial Patterns: A Hybrid Learning Approach","display_name":"DRAM Failure Prediction with Correctable Error Spatial Patterns: A Hybrid Learning Approach","publication_year":2025,"publication_date":"2025-11-19","ids":{"openalex":"https://openalex.org/W7123568625","doi":"https://doi.org/10.1145/3772052.3772234"},"language":null,"primary_location":{"id":"doi:10.1145/3772052.3772234","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3772052.3772234","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 ACM Symposium on Cloud Computing","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/A5122991014","display_name":"Lei Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144143","display_name":"Inspur (China)","ror":"https://ror.org/0474p4r72","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210144143"]},{"id":"https://openalex.org/I4210144487","display_name":"Cloud Computing Center","ror":"https://ror.org/04aa0zm65","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210144487"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Liu","raw_affiliation_strings":["Inspur Cloud Information Technology Co., Ltd., Jinan, China"],"raw_orcid":"https://orcid.org/0009-0003-2538-8515","affiliations":[{"raw_affiliation_string":"Inspur Cloud Information Technology Co., Ltd., Jinan, China","institution_ids":["https://openalex.org/I4210144487","https://openalex.org/I4210144143"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yinling Zhang","orcid":"https://orcid.org/0009-0002-0726-8520"},"institutions":[{"id":"https://openalex.org/I4210123254","display_name":"Thermal Power Research Institute","ror":"https://ror.org/020jz8z49","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123254"]},{"id":"https://openalex.org/I4210152501","display_name":"China Power Engineering Consulting Group (China)","ror":"https://ror.org/04t59qd02","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210152501"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinling Zhang","raw_affiliation_strings":["JINAN THERMAL POWER GROUP CO. LTD, Jinan, China"],"raw_orcid":"https://orcid.org/0009-0002-0726-8520","affiliations":[{"raw_affiliation_string":"JINAN THERMAL POWER GROUP CO. LTD, Jinan, China","institution_ids":["https://openalex.org/I4210123254","https://openalex.org/I4210152501"]}]}],"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":0.63526626,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"299","last_page":"306"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.4948999881744385,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.4948999881744385,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.3231000006198883,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.02889999933540821,"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/dram","display_name":"Dram","score":0.8805000185966492},{"id":"https://openalex.org/keywords/downtime","display_name":"Downtime","score":0.8669999837875366},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6758000254631042},{"id":"https://openalex.org/keywords/unavailability","display_name":"Unavailability","score":0.5722000002861023},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5254999995231628},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.40230000019073486},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39419999718666077},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.39160001277923584}],"concepts":[{"id":"https://openalex.org/C7366592","wikidata":"https://www.wikidata.org/wiki/Q1255620","display_name":"Dram","level":2,"score":0.8805000185966492},{"id":"https://openalex.org/C180591934","wikidata":"https://www.wikidata.org/wiki/Q1253369","display_name":"Downtime","level":2,"score":0.8669999837875366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7109000086784363},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6758000254631042},{"id":"https://openalex.org/C2780505938","wikidata":"https://www.wikidata.org/wiki/Q17093282","display_name":"Unavailability","level":2,"score":0.5722000002861023},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5254999995231628},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.461899995803833},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.4165000021457672},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.40230000019073486},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.396699994802475},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39419999718666077},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.39160001277923584},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.38609999418258667},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3792000114917755},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.37700000405311584},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.36739999055862427},{"id":"https://openalex.org/C153740404","wikidata":"https://www.wikidata.org/wiki/Q671224","display_name":"Data center","level":2,"score":0.3564000129699707},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.3116999864578247},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C118702147","wikidata":"https://www.wikidata.org/wiki/Q189396","display_name":"Dynamic random-access memory","level":3,"score":0.29109999537467957},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.28540000319480896},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.25110000371932983},{"id":"https://openalex.org/C185177783","wikidata":"https://www.wikidata.org/wiki/Q3332814","display_name":"Megabit","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3772052.3772234","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3772052.3772234","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 ACM Symposium on Cloud Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5355897545814514,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2089316943","https://openalex.org/W2142812297","https://openalex.org/W2194775991","https://openalex.org/W2772956929","https://openalex.org/W2908177913","https://openalex.org/W2945142706","https://openalex.org/W3009207130","https://openalex.org/W3132629440","https://openalex.org/W3167937798","https://openalex.org/W3205272658","https://openalex.org/W4283077289","https://openalex.org/W4313451571","https://openalex.org/W4318147164","https://openalex.org/W4321636490","https://openalex.org/W4385688947","https://openalex.org/W4389163020","https://openalex.org/W4389491852","https://openalex.org/W4396909910","https://openalex.org/W4400810474","https://openalex.org/W4401753306"],"related_works":[],"abstract_inverted_index":{"Dynamic":[0],"Random":[1],"Access":[2],"Memory":[3],"(DRAM)":[4],"failures":[5,18],"are":[6],"a":[7,32,54],"leading":[8],"cause":[9],"of":[10,42],"server":[11],"downtime":[12,21],"in":[13],"cloud":[14,113],"centers.":[15],"Predicting":[16],"DRAM":[17,34,97],"could":[19],"reduce":[20],"events,":[22],"avoiding":[23],"data":[24,115],"loss":[25],"and":[26,82,87],"industry":[27],"damage.":[28],"In":[29],"this":[30],"study,":[31],"novel":[33],"failure":[35],"prediction":[36],"method":[37],"based":[38],"on":[39,103],"spatial":[40,73],"patterns":[41],"Correctable":[43],"Errors":[44],"(CEs)":[45],"was":[46,68],"proposed.":[47],"After":[48,99],"reconstructing":[49],"the":[50,104],"CE":[51],"information":[52],"into":[53],"feature":[55,77],"map,":[56],"effective":[57],"artificial":[58],"features":[59],"were":[60,90],"extracted.":[61],"And":[62],"an":[63],"innovative":[64],"3D":[65],"CWT-PCA":[66],"transform":[67],"proposed":[69],"to":[70,95],"render":[71],"its":[72],"patterns.":[74],"We":[75],"explored":[76],"importance":[78],"using":[79],"SHAP":[80],"analysis":[81],"visualisation":[83],"techniques.":[84],"Then,":[85],"ResNet":[86],"KAN":[88],"networks":[89],"employed":[91],"for":[92,116],"hybrid":[93],"learning":[94],"predict":[96],"failures.":[98],"achieving":[100],"promising":[101],"results":[102],"publicly":[105],"available":[106],"Large-scale":[107],"Dataset,":[108],"we":[109],"further":[110],"collected":[111],"real-world":[112],"center":[114],"generalization":[117],"validation.":[118]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-14T00:00:00"}