{"id":"https://openalex.org/W7169867394","doi":"https://doi.org/10.48550/arxiv.2607.16784","title":"Roomie: Interference-Aware Colocation for Efficient Model Serving","display_name":"Roomie: Interference-Aware Colocation for Efficient Model Serving","publication_year":2026,"publication_date":"2026-07-18","ids":{"openalex":"https://openalex.org/W7169867394","doi":"https://doi.org/10.48550/arxiv.2607.16784"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.16784","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.16784","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.16784","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135520532","display_name":"Youssouph Faye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Faye, Youssouph","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002267438","display_name":"Francescomaria Faticanti","orcid":"https://orcid.org/0000-0002-3075-313X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Faticanti, Francescomaria","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107170917","display_name":"S Jain","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jain, Shubham","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5017386836","display_name":"Francesco Bronzino","orcid":"https://orcid.org/0000-0003-4447-960X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bronzino, Francesco","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.32089999318122864,"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":0.32089999318122864,"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":0.20350000262260437,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.06909999996423721,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/goodput","display_name":"Goodput","score":0.7878999710083008},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6309999823570251},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6079000234603882},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5159000158309937},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4438999891281128},{"id":"https://openalex.org/keywords/profiling","display_name":"Profiling (computer programming)","score":0.4399999976158142},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.38519999384880066},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.382999986410141},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.37400001287460327}],"concepts":[{"id":"https://openalex.org/C94022561","wikidata":"https://www.wikidata.org/wiki/Q1172393","display_name":"Goodput","level":4,"score":0.7878999710083008},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7799000144004822},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6309999823570251},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6079000234603882},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5159000158309937},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4438999891281128},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.4399999976158142},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.40400001406669617},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38580000400543213},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.38519999384880066},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.382999986410141},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.37400001287460327},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.33719998598098755},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.3337000012397766},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.32910001277923584},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.31690001487731934},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3163999915122986},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C70388272","wikidata":"https://www.wikidata.org/wiki/Q5968558","display_name":"IBM","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C2780102126","wikidata":"https://www.wikidata.org/wiki/Q10928179","display_name":"Online and offline","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.2662999927997589},{"id":"https://openalex.org/C124978682","wikidata":"https://www.wikidata.org/wiki/Q1201019","display_name":"Proof of concept","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.259799987077713},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.258899986743927},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.16784","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.16784","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.16784","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.16784","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"demand":[1],"for":[2],"DNN":[3],"inference":[4,173],"grows,":[5],"GPU":[6,144],"capacity":[7],"is":[8],"increasingly":[9],"oversubscribed,":[10],"forcing":[11],"operators":[12],"to":[13,61,96,110,137,142,177,189],"colocate":[14],"multiple":[15],"models":[16,43],"on":[17,34],"the":[18,35,143],"same":[19],"device":[20],"in":[21,122,183],"both":[22,158],"cloud":[23],"and":[24,76,101,128,162,182],"edge":[25,164],"deployments.":[26],"Whether":[27],"colocation":[28],"succeeds":[29],"or":[30,53],"violates":[31],"SLOs":[32],"depends":[33],"temporal":[36,63],"overlap":[37],"of":[38],"kernels":[39],"from":[40,88],"concurrently":[41],"executing":[42],"--":[44],"an":[45,105,129],"effect":[46],"that":[47,59,74,145,167],"existing":[48,190],"serving":[49,71],"systems":[50],"either":[51],"ignore":[52],"approximate":[54],"using":[55],"aggregate":[56],"resource":[57,99],"profiles":[58],"fail":[60],"capture":[62],"dynamics.":[64],"This":[65],"paper":[66],"presents":[67],"Roomie,":[68],"a":[69],"model":[70,108,141],"orchestration":[72],"architecture":[73],"predicts":[75,102],"avoids":[77],"kernel-level":[78],"interference":[79,90,103,121],"between":[80],"colocated":[81],"DNNs.":[82],"Roomie":[83,153,168],"decouples":[84],"offline":[85],"kernel":[86],"profiling":[87,94],"online":[89,130],"prediction.":[91],"It":[92],"uses":[93,134],"only":[95],"extract":[97],"per-kernel":[98],"configurations,":[100],"with":[104],"occupancy-based":[106],"analytical":[107],"immune":[109],"profiler-induced":[111],"timing":[112],"distortion.":[113],"A":[114],"pairwise":[115],"greedy":[116],"heuristic":[117],"then":[118,133],"approximates":[119],"multi-model":[120],"polynomial":[123],"rather":[124],"than":[125],"exponential":[126],"time,":[127],"placement":[131],"algorithm":[132],"these":[135],"estimates":[136],"assign":[138],"each":[139],"incoming":[140],"minimizes":[146],"predicted":[147],"slowdown.":[148],"Our":[149],"experimental":[150],"evaluation":[151],"compares":[152],"against":[154],"state-of-the-art":[155],"solutions":[156],"across":[157],"cloud-grade":[159],"server":[160],"clusters":[161],"embedded":[163],"devices,":[165],"demonstrating":[166],"reduces":[169],"SLO":[170],"violations":[171],"(i.e.,":[172],"latency)":[174],"by":[175],"up":[176],"3x,":[178],"while":[179],"maintaining":[180],"comparable,":[181],"many":[184],"cases":[185],"superior,":[186],"goodput":[187],"relative":[188],"approaches.":[191]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-22T00:00:00"}
