{"id":"https://openalex.org/W4416203789","doi":"https://doi.org/10.1145/3712285.3759879","title":"Minimizing Power Waste in Heterogenous Computing via Adaptive Uncore Scaling","display_name":"Minimizing Power Waste in Heterogenous Computing via Adaptive Uncore Scaling","publication_year":2025,"publication_date":"2025-11-12","ids":{"openalex":"https://openalex.org/W4416203789","doi":"https://doi.org/10.1145/3712285.3759879"},"language":null,"primary_location":{"id":"doi:10.1145/3712285.3759879","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3712285.3759879","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis","raw_type":"proceedings-article"},"type":"conference-paper","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/A5038312700","display_name":"Zhong Zheng","orcid":"https://orcid.org/0009-0006-6617-649X"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhong Zheng","raw_affiliation_strings":["University of Illinois Chicago, Chicago, USA"],"raw_orcid":"https://orcid.org/0009-0006-6617-649X","affiliations":[{"raw_affiliation_string":"University of Illinois Chicago, Chicago, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090323629","display_name":"Seyfal Sultanov","orcid":"https://orcid.org/0009-0005-4948-7811"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Seyfal Sultanov","raw_affiliation_strings":["University of Illinois Chicago, Chicago, USA"],"raw_orcid":"https://orcid.org/0009-0005-4948-7811","affiliations":[{"raw_affiliation_string":"University of Illinois Chicago, Chicago, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010928934","display_name":"Michael E. Papka","orcid":"https://orcid.org/0000-0002-6418-5767"},"institutions":[{"id":"https://openalex.org/I1282105669","display_name":"Argonne National Laboratory","ror":"https://ror.org/05gvnxz63","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282105669","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I40347166"]},{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael E. Papka","raw_affiliation_strings":["Argonne National Laboratory (ANL), Lemont, USA and University of Illinois Chicago, Chicago, USA"],"raw_orcid":"https://orcid.org/0000-0002-6418-5767","affiliations":[{"raw_affiliation_string":"Argonne National Laboratory (ANL), Lemont, USA and University of Illinois Chicago, Chicago, USA","institution_ids":["https://openalex.org/I1282105669","https://openalex.org/I39422238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060400468","display_name":"Zhiling Lan","orcid":"https://orcid.org/0000-0002-1047-8724"},"institutions":[{"id":"https://openalex.org/I1282105669","display_name":"Argonne National Laboratory","ror":"https://ror.org/05gvnxz63","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282105669","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I40347166"]},{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiling Lan","raw_affiliation_strings":["University of Illinois Chicago, Chicago, USA and Argonne National Laboratory (ANL), Lemont, USA"],"raw_orcid":"https://orcid.org/0000-0002-1047-8724","affiliations":[{"raw_affiliation_string":"University of Illinois Chicago, Chicago, USA and Argonne National Laboratory (ANL), Lemont, USA","institution_ids":["https://openalex.org/I1282105669","https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5151,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.83744038,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"505","last_page":"518"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9502999782562256,"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"}},"topics":[{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9502999782562256,"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/T14347","display_name":"Big Data and Digital Economy","score":0.011300000362098217,"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/T10363","display_name":"Low-power high-performance VLSI design","score":0.007899999618530273,"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/frequency-scaling","display_name":"Frequency scaling","score":0.7437999844551086},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.722599983215332},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5782999992370605},{"id":"https://openalex.org/keywords/supercomputer","display_name":"Supercomputer","score":0.536899983882904},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.46380001306533813},{"id":"https://openalex.org/keywords/central-processing-unit","display_name":"Central processing unit","score":0.4251999855041504},{"id":"https://openalex.org/keywords/power-management","display_name":"Power management","score":0.4228000044822693},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.41519999504089355}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7742999792098999},{"id":"https://openalex.org/C157742956","wikidata":"https://www.wikidata.org/wiki/Q3237776","display_name":"Frequency scaling","level":3,"score":0.7437999844551086},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.722599983215332},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5782999992370605},{"id":"https://openalex.org/C83283714","wikidata":"https://www.wikidata.org/wiki/Q121117","display_name":"Supercomputer","level":2,"score":0.536899983882904},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.46380001306533813},{"id":"https://openalex.org/C49154492","wikidata":"https://www.wikidata.org/wiki/Q5300","display_name":"Central processing unit","level":2,"score":0.4251999855041504},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.42419999837875366},{"id":"https://openalex.org/C2778774385","wikidata":"https://www.wikidata.org/wiki/Q4437810","display_name":"Power management","level":3,"score":0.4228000044822693},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.41519999504089355},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.40689998865127563},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.35690000653266907},{"id":"https://openalex.org/C172430144","wikidata":"https://www.wikidata.org/wiki/Q17111997","display_name":"Symmetric multiprocessor system","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.3345000147819519},{"id":"https://openalex.org/C512564126","wikidata":"https://www.wikidata.org/wiki/Q7257959","display_name":"Public records","level":2,"score":0.32589998841285706},{"id":"https://openalex.org/C2989134064","wikidata":"https://www.wikidata.org/wiki/Q288510","display_name":"Execution time","level":2,"score":0.31209999322891235},{"id":"https://openalex.org/C118993495","wikidata":"https://www.wikidata.org/wiki/Q5042828","display_name":"Electrical efficiency","level":3,"score":0.29339998960494995},{"id":"https://openalex.org/C31352089","wikidata":"https://www.wikidata.org/wiki/Q3750474","display_name":"Systems design","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C118021083","wikidata":"https://www.wikidata.org/wiki/Q610398","display_name":"System on a chip","level":2,"score":0.25600001215934753},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.25220000743865967},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3712285.3759879","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3712285.3759879","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis","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":39,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1965679570","https://openalex.org/W1977661221","https://openalex.org/W1979596095","https://openalex.org/W1986989509","https://openalex.org/W2031136586","https://openalex.org/W2032512814","https://openalex.org/W2060728378","https://openalex.org/W2160804075","https://openalex.org/W2171268876","https://openalex.org/W2414869006","https://openalex.org/W2609332365","https://openalex.org/W2733949682","https://openalex.org/W2790721814","https://openalex.org/W2790957308","https://openalex.org/W2793320545","https://openalex.org/W2794513473","https://openalex.org/W2907659537","https://openalex.org/W2933483662","https://openalex.org/W2962843187","https://openalex.org/W2971469712","https://openalex.org/W2983811377","https://openalex.org/W2997958863","https://openalex.org/W3011015184","https://openalex.org/W3037110041","https://openalex.org/W3087939472","https://openalex.org/W3097287637","https://openalex.org/W3143049562","https://openalex.org/W3206857466","https://openalex.org/W4200184446","https://openalex.org/W4285703967","https://openalex.org/W4312580880","https://openalex.org/W4386707690","https://openalex.org/W4386709569","https://openalex.org/W4388561528","https://openalex.org/W4388661790","https://openalex.org/W4401474635","https://openalex.org/W4401723357","https://openalex.org/W4404133446"],"related_works":[],"abstract_inverted_index":{"High-performance":[0],"computing":[1,95],"(HPC)":[2],"systems":[3,22,96,176],"are":[4],"essential":[5],"for":[6,113],"scientific":[7],"discovery":[8],"and":[9,63,147,158,171,180,208],"engineering":[10],"innovation.":[11],"However,":[12],"their":[13],"growing":[14],"power":[15,78,83,99,129,161],"demands":[16],"pose":[17],"significant":[18],"challenges,":[19],"particularly":[20],"as":[21],"scale":[23],"to":[24,61,122,190,195],"the":[25,196],"exascale":[26],"level.":[27],"Prior":[28],"uncore":[29,65,71,109,119,136],"frequency":[30,72,110],"tuning":[31],"studies":[32],"have":[33],"primarily":[34],"focused":[35],"on":[36,41,54,173],"conventional":[37],"HPC":[38,45],"workloads":[39,53],"running":[40],"CPU-only":[42],"systems.":[43],"As":[44,91],"advances":[46],"toward":[47],"heterogeneous":[48,55,114,175],"computing,":[49],"integrating":[50],"diverse":[51],"GPU":[52,169,181],"CPU-GPU":[56],"systems,":[57],"it":[58],"becomes":[59],"imperative":[60],"revisit":[62],"enhance":[64],"scaling.":[66],"Our":[67,138],"investigation":[68],"reveals":[69],"that":[70,186],"scales":[73],"down":[74],"only":[75],"when":[76],"CPU":[77,179],"approaches":[79],"its":[80],"thermal":[81],"design":[82,139],"(TDP),":[84],"which":[85],"is":[86],"rare":[87],"in":[88],"GPU-dominant":[89],"applications.":[90],"a":[92,107,201],"result,":[93],"modern":[94],"experience":[97],"unnecessary":[98],"waste.":[100],"In":[101],"this":[102],"study,":[103],"we":[104],"present":[105],"MAGUS,":[106],"user-transparent":[108],"scaling":[111],"runtime":[112],"computing.":[115],"MAGUS":[116,166,187],"dynamically":[117],"adjusts":[118],"frequencies":[120],"according":[121],"distinct":[123],"application":[124],"execution":[125],"phases,":[126],"effectively":[127],"minimizing":[128],"waste":[130],"caused":[131],"by":[132],"consistently":[133],"using":[134],"maximum":[135],"frequencies.":[137],"incorporates":[140],"several":[141],"key":[142],"techniques,":[143],"including":[144],"real-time":[145],"monitoring":[146],"prediction":[148],"of":[149,154,204,211],"memory":[150],"accesses,":[151],"intelligent":[152],"handling":[153],"frequent":[155],"phase":[156],"transitions,":[157],"leveraging":[159],"vendor-provided":[160],"management":[162],"features.":[163],"We":[164],"evaluate":[165],"with":[167,177],"various":[168],"benchmarks":[170],"applications":[172],"multiple":[174],"different":[178],"architectures.":[182],"Experimental":[183],"results":[184],"demonstrate":[185],"achieves":[188],"up":[189],"27%":[191],"energy":[192],"savings":[193],"compared":[194],"default":[197],"settings,":[198],"while":[199],"maintaining":[200],"performance":[202],"loss":[203],"less":[205],"than":[206],"5%":[207],"an":[209],"overhead":[210],"under":[212],"1%.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-11-12T00:00:00"}