{"id":"https://openalex.org/W7135047864","doi":"https://doi.org/10.48550/arxiv.2603.10342","title":"AgentServe: Algorithm-System Co-Design for Efficient Agentic AI Serving on a Consumer-Grade GPU","display_name":"AgentServe: Algorithm-System Co-Design for Efficient Agentic AI Serving on a Consumer-Grade GPU","publication_year":2026,"publication_date":"2026-03-11","ids":{"openalex":"https://openalex.org/W7135047864","doi":"https://doi.org/10.48550/arxiv.2603.10342"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.10342","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10342","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.10342","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039364773","display_name":"Yuning Zhang","orcid":"https://orcid.org/0000-0002-0306-1859"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang, Yuning","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128877939","display_name":"Yan Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Yan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128830416","display_name":"Nan Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Nan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128851164","display_name":"Dong Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Dong","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5039364773"],"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/T14347","display_name":"Big Data and Digital Economy","score":0.29789999127388,"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/T14347","display_name":"Big Data and Digital Economy","score":0.29789999127388,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.0869000032544136,"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"}},{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.08240000158548355,"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/interleaving","display_name":"Interleaving","score":0.5364999771118164},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5232999920845032},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5056999921798706},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.48350000381469727},{"id":"https://openalex.org/keywords/context-switch","display_name":"Context switch","score":0.44589999318122864},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.414900004863739},{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.3921999931335449},{"id":"https://openalex.org/keywords/allocator","display_name":"Allocator","score":0.3698999881744385},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.36739999055862427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8831999897956848},{"id":"https://openalex.org/C28034677","wikidata":"https://www.wikidata.org/wiki/Q17092530","display_name":"Interleaving","level":2,"score":0.5364999771118164},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5232999920845032},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5056999921798706},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.48350000381469727},{"id":"https://openalex.org/C53833338","wikidata":"https://www.wikidata.org/wiki/Q1061424","display_name":"Context switch","level":2,"score":0.44589999318122864},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.414900004863739},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.3921999931335449},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.3919999897480011},{"id":"https://openalex.org/C162262903","wikidata":"https://www.wikidata.org/wiki/Q343527","display_name":"Allocator","level":2,"score":0.3698999881744385},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.36739999055862427},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3594000041484833},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.35850000381469727},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.35359999537467957},{"id":"https://openalex.org/C2778119891","wikidata":"https://www.wikidata.org/wiki/Q477690","display_name":"CUDA","level":2,"score":0.353300005197525},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.33820000290870667},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.3352999985218048},{"id":"https://openalex.org/C2778565505","wikidata":"https://www.wikidata.org/wiki/Q2207566","display_name":"Spec#","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C169590947","wikidata":"https://www.wikidata.org/wiki/Q47506","display_name":"Compiler","level":2,"score":0.3183000087738037},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.31610000133514404},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.31529998779296875},{"id":"https://openalex.org/C144745244","wikidata":"https://www.wikidata.org/wiki/Q4927286","display_name":"Blocking (statistics)","level":2,"score":0.3140999972820282},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C2779041454","wikidata":"https://www.wikidata.org/wiki/Q870780","display_name":"Chatbot","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C2781020372","wikidata":"https://www.wikidata.org/wiki/Q533093","display_name":"On the fly","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2833999991416931},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2694999873638153},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.25380000472068787},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.25209999084472656},{"id":"https://openalex.org/C204854418","wikidata":"https://www.wikidata.org/wiki/Q1362921","display_name":"Polling","level":2,"score":0.25189998745918274},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.10342","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10342","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.10342","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10342","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"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":{"Large":[0],"language":[1,58],"models":[2,59],"(LLMs)":[3],"are":[4,127],"increasingly":[5],"deployed":[6],"as":[7],"AI":[8,48],"agents":[9],"that":[10,91,101,145,180],"operate":[11],"in":[12],"short":[13,83,124],"reasoning-action":[14],"loops,":[15],"interleaving":[16],"model":[17],"computation":[18],"with":[19,174],"external":[20],"calls.":[21],"Unlike":[22],"traditional":[23],"chat":[24],"applications,":[25],"these":[26],"agentic":[27],"workloads":[28],"require":[29],"inference":[30],"serving":[31,143],"systems":[32],"to":[33,120,134,161,192],"balance":[34],"low":[35],"latency,":[36],"stable":[37,147],"token":[38],"emission,":[39],"and":[40,69,82,123,164,196],"throughput":[41],"under":[42,150],"multiple":[43],"request":[44],"arrivals":[45],"from":[46,156],"different":[47,204],"agents.":[49],"Recent":[50],"deployments":[51],"highlight":[52],"a":[53,77,141],"shift":[54],"toward":[55],"running":[56],"small":[57],"(SLMs)":[60],"locally":[61],"on":[62,76],"consumer-grade":[63],"GPUs,":[64],"driven":[65],"by":[66,153],"privacy,":[67],"compliance,":[68],"cost":[70],"constraints.":[71],"When":[72],"heterogeneous":[73],"requests":[74],"overlap":[75],"single":[78],"GPU,":[79],"long":[80,111],"prefills":[81,155],"decodes":[84],"contend":[85],"for":[86],"resources,":[87],"creating":[88],"head-of-line":[89],"blocking":[90],"destabilizes":[92],"interactive":[93],"performance.":[94],"By":[95],"analyzing":[96],"agent":[97],"workloads,":[98],"we":[99],"observe":[100],"their":[102],"execution":[103,149],"naturally":[104],"separates":[105],"into":[106],"cold":[107],"prefills,":[108,115,163],"which":[109,116,126],"process":[110],"system":[112,144],"prompts,":[113],"resume":[114,162],"append":[117],"tool":[118],"outputs":[119],"cached":[121],"contexts,":[122],"decodes,":[125,157],"latency-critical.":[128],"This":[129],"mix":[130],"intensifies":[131],"contention":[132],"compared":[133],"conventional":[135],"chatbot":[136],"serving.":[137],"We":[138],"present":[139],"AgentServe,":[140],"single-GPU":[142],"ensures":[146],"multi-agent":[148],"such":[151],"conditions":[152],"isolating":[154],"applying":[158],"dynamic":[159],"budgeting":[160],"allocating":[165],"GPU":[166],"resources":[167],"through":[168],"pre-established":[169],"CUDA":[170],"Green":[171],"Context":[172],"slots":[173],"adaptive":[175],"control.":[176],"Evaluation":[177],"results":[178],"show":[179],"AgentServe":[181],"significantly":[182],"improves":[183],"latency":[184],"stability":[185],"while":[186],"sustaining":[187],"competitive":[188],"throughput,":[189],"achieving":[190],"up":[191],"2.8x":[193],"TTFT":[194],"improvement":[195,199],"2.7x":[197],"TPOT":[198],"over":[200],"state-of-the-art":[201],"baselines":[202],"across":[203],"settings.":[205]},"counts_by_year":[],"updated_date":"2026-03-13T14:25:03.468858","created_date":"2026-03-13T00:00:00"}
