{"id":"https://openalex.org/W4414736129","doi":"https://doi.org/10.1145/3731569.3764846","title":"COpter: Efficient Large-Scale Resource-Allocation via Continual Optimization","display_name":"COpter: Efficient Large-Scale Resource-Allocation via Continual Optimization","publication_year":2025,"publication_date":"2025-10-01","ids":{"openalex":"https://openalex.org/W4414736129","doi":"https://doi.org/10.1145/3731569.3764846"},"language":"en","primary_location":{"id":"doi:10.1145/3731569.3764846","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3731569.3764846","pdf_url":null,"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 ACM SIGOPS 31st Symposium on Operating Systems Principles","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3731569.3764846","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013776746","display_name":"Suhas Jayaram Subramanya","orcid":"https://orcid.org/0009-0001-8013-461X"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suhas Jayaram Subramanya","raw_affiliation_strings":["Computer Science Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA","Microsoft, Seattle, Washington, USA"],"raw_orcid":"https://orcid.org/0009-0001-8013-461X","affiliations":[{"raw_affiliation_string":"Computer Science Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Microsoft, Seattle, Washington, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003148257","display_name":"Don Kurian Dennis","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]},{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Don Kurian Dennis","raw_affiliation_strings":["Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA","Meta Platforms, Inc., Menlo Park, California, USA"],"raw_orcid":"https://orcid.org/0009-0007-2941-592X","affiliations":[{"raw_affiliation_string":"Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Meta Platforms, Inc., Menlo Park, California, USA","institution_ids":["https://openalex.org/I4210114444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112800069","display_name":"Virginia Smith","orcid":"https://orcid.org/0000-0002-6404-2395"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Virginia Smith","raw_affiliation_strings":["Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA"],"raw_orcid":"https://orcid.org/0000-0002-6404-2395","affiliations":[{"raw_affiliation_string":"Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037557529","display_name":"Gregory R. Ganger","orcid":"https://orcid.org/0000-0002-3065-7316"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gregory R. Ganger","raw_affiliation_strings":["Electrical and Computer Engineering Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA"],"raw_orcid":"https://orcid.org/0000-0002-3065-7316","affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"322","last_page":"340"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9983999729156494,"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"}},"topics":[{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9983999729156494,"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/T10714","display_name":"Software-Defined Networks and 5G","score":0.9983000159263611,"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/T12288","display_name":"Optimization and Search Problems","score":0.9980000257492065,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.7264999747276306},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.6744999885559082},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.6205999851226807},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.487199991941452},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4341999888420105},{"id":"https://openalex.org/keywords/integer-programming","display_name":"Integer programming","score":0.420199990272522},{"id":"https://openalex.org/keywords/linear-programming","display_name":"Linear programming","score":0.4002000093460083},{"id":"https://openalex.org/keywords/resource-management","display_name":"Resource management (computing)","score":0.39980000257492065}],"concepts":[{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.7264999747276306},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7232999801635742},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.6744999885559082},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6704999804496765},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.6205999851226807},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.487199991941452},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4341999888420105},{"id":"https://openalex.org/C56086750","wikidata":"https://www.wikidata.org/wiki/Q6042592","display_name":"Integer programming","level":2,"score":0.420199990272522},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.4002000093460083},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.39980000257492065},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.39910000562667847},{"id":"https://openalex.org/C162262903","wikidata":"https://www.wikidata.org/wiki/Q343527","display_name":"Allocator","level":2,"score":0.3880999982357025},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.3547999858856201},{"id":"https://openalex.org/C97137487","wikidata":"https://www.wikidata.org/wiki/Q729138","display_name":"Integer (computer science)","level":2,"score":0.3163999915122986},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.3052000105381012},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.25519999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3731569.3764846","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3731569.3764846","pdf_url":null,"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 ACM SIGOPS 31st Symposium on Operating Systems Principles","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3731569.3764846","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3731569.3764846","pdf_url":null,"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 ACM SIGOPS 31st Symposium on Operating Systems Principles","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1058890252","display_name":"CNS: Medium: Ground up Adaptive Learning System for Heterogeneous Environments","funder_award_id":"2211882","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3498504188","display_name":null,"funder_award_id":"W911NF-20- D-0002","funder_id":"https://openalex.org/F4320332447","funder_display_name":"U.S. Army"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332447","display_name":"U.S. Army","ror":"https://ror.org/00afsp483"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W95608104","https://openalex.org/W105472389","https://openalex.org/W1516019649","https://openalex.org/W2027826061","https://openalex.org/W2091010238","https://openalex.org/W2098095723","https://openalex.org/W2117595194","https://openalex.org/W2198183204","https://openalex.org/W2271870283","https://openalex.org/W2734941459","https://openalex.org/W2769646558","https://openalex.org/W2912274232","https://openalex.org/W2912894509","https://openalex.org/W2963956318","https://openalex.org/W2992727511","https://openalex.org/W3101798601","https://openalex.org/W4200208024","https://openalex.org/W4205841652","https://openalex.org/W4230033334","https://openalex.org/W4236202168","https://openalex.org/W4244393449","https://openalex.org/W4287122887","https://openalex.org/W4292363360","https://openalex.org/W4293775970","https://openalex.org/W4297825594","https://openalex.org/W4308995001","https://openalex.org/W4386875093","https://openalex.org/W4387302738","https://openalex.org/W4413757026","https://openalex.org/W6949488649"],"related_works":[],"abstract_inverted_index":{"Optimization-based":[0],"resource":[1,38,51,86],"allocation":[2,11,39,52,87,178],"in":[3,137],"large-scale":[4],"systems":[5],"often":[6,54],"must":[7],"trade-off":[8],"responsiveness":[9],"and":[10,24,78,114,116,146,180],"quality.":[12],"Generally,":[13],"allocations":[14],"are":[15],"reconsidered":[16],"every":[17],"few":[18],"minutes":[19],"(a":[20],"round)":[21],"by":[22,57,89,162,185],"formulating":[23],"solving":[25,65],"a":[26,41,69,102],"new":[27],"optimization":[28,73],"problem.":[29],"This":[30],"paper":[31],"introduces":[32],"continual":[33,72],"optimization,":[34],"which":[35],"reframes":[36],"round-based":[37],"as":[40],"sequence":[42],"of":[43,74,85],"interconnected":[44],"problems,":[45],"leveraging":[46],"the":[47],"observation":[48],"that":[49,106,123,153],"these":[50],"problems":[53,88,122,136],"only":[55],"change":[56],"small":[58],"amounts":[59],"across":[60],"successive":[61],"rounds":[62],"to":[63,165,170],"reduce":[64],"times.":[66],"COpter":[67,134,154,175],"provides":[68],"method":[70,104],"for":[71,98,120],"Linear":[75,81],"Programs":[76,82],"(LP)":[77],"Mixed":[79],"Integer":[80],"(MILP)":[83],"formulations":[84],"combining":[90],"three":[91,138],"innovations:":[92],"(1)":[93],"an":[94],"efficient-to-update":[95],"problem":[96,171],"representation":[97],"incremental":[99],"changes,":[100],"(2)":[101],"proximal-point":[103],"implementation":[105],"can":[107],"provably":[108],"benefit":[109],"from":[110],"prior":[111],"computational":[112],"effort":[113],"allocations,":[115],"(3)":[117],"lightweight":[118],"heuristics":[119],"mixed-integer":[121],"recover":[124],"feasible":[125],"integer":[126],"solutions":[127,157],"with":[128],"negligible":[129],"quality":[130,179],"loss.":[131],"We":[132],"evaluate":[133],"on":[135],"domains:":[139],"GPU":[140],"cluster":[141],"scheduling,":[142],"shard":[143],"load":[144],"balancing,":[145],"WAN":[147],"traffic":[148],"engineering.":[149],"Overall,":[150],"we":[151],"find":[152],"finds":[155],"high-quality":[156],"while":[158],"reducing":[159],"solver":[160],"runtimes":[161,184],"57\u201383\u00d7":[163],"compared":[164],"state-of-the-art":[166],"commercial":[167],"solvers.":[168],"Compared":[169],"partitioning":[172],"approaches":[173],"(POP),":[174],"simultaneously":[176],"improves":[177],"reduces":[181],"end-to-end":[182],"allocator":[183],"1.5\u201330\u00d7.":[186]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}