{"id":"https://openalex.org/W7162459074","doi":"https://doi.org/10.48550/arxiv.2605.25247","title":"Kavier: Exploring Performance, Sustainability, and Efficiency of LLM Ecosystems under Inference through Cache-Aware Discrete-Event Simulation","display_name":"Kavier: Exploring Performance, Sustainability, and Efficiency of LLM Ecosystems under Inference through Cache-Aware Discrete-Event Simulation","publication_year":2026,"publication_date":"2026-05-24","ids":{"openalex":"https://openalex.org/W7162459074","doi":"https://doi.org/10.48550/arxiv.2605.25247"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.25247","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25247","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.25247","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137041098","display_name":"Radu Nicolae","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nicolae, Radu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006986556","display_name":"Alexandru Iosup","orcid":"https://orcid.org/0000-0001-8030-9398"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Iosup, Alexandru","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002623098","display_name":"Animesh Trivedi","orcid":"https://orcid.org/0000-0003-3586-7168"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Trivedi, Animesh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5076494860","display_name":"Jesse Donkervliet","orcid":"https://orcid.org/0000-0002-3067-6402"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Donkervliet, Jesse","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/T11948","display_name":"Machine Learning in Materials Science","score":0.3034999966621399,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.3034999966621399,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.09570000320672989,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.07620000094175339,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6345000267028809},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5774999856948853},{"id":"https://openalex.org/keywords/prefix","display_name":"Prefix","score":0.364300012588501},{"id":"https://openalex.org/keywords/macro","display_name":"Macro","score":0.3352000117301941},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.3330000042915344},{"id":"https://openalex.org/keywords/ecosystem","display_name":"Ecosystem","score":0.3111000061035156}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7360000014305115},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6345000267028809},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5774999856948853},{"id":"https://openalex.org/C141603448","wikidata":"https://www.wikidata.org/wiki/Q134830","display_name":"Prefix","level":2,"score":0.364300012588501},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.34540000557899475},{"id":"https://openalex.org/C166955791","wikidata":"https://www.wikidata.org/wiki/Q629579","display_name":"Macro","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3330000042915344},{"id":"https://openalex.org/C110872660","wikidata":"https://www.wikidata.org/wiki/Q37813","display_name":"Ecosystem","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28859999775886536},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.2854999899864197},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.27559998631477356},{"id":"https://openalex.org/C108215451","wikidata":"https://www.wikidata.org/wiki/Q7263963","display_name":"Simulation modeling","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C76178495","wikidata":"https://www.wikidata.org/wiki/Q4808784","display_name":"Asset (computer security)","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2660999894142151},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.25619998574256897},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.25247","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25247","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.25247","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25247","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":"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":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"are":[4],"widely":[5],"used":[6],"by":[7,62],"our":[8],"increasingly":[9],"digitalized":[10],"society,":[11],"but":[12],"raise":[13],"sustainability,":[14,153,211],"performance,":[15,152,210,239],"and":[16,28,36,83,88,124,154,163,169,180,190,205,212,230,240],"financial":[17],"concerns,":[18],"especially":[19],"as":[20],"inference":[21],"workloads":[22],"grow.":[23],"To":[24],"improve":[25],"the":[26,63,73,86,95,117,138,144,151,186,199,209],"design":[27,142],"operation":[29],"of":[30,65,70,75,130,156,188,201,214],"LLM":[31,44,71,106,131,157,215,234],"ecosystems,":[32],"we":[33,111,121,141,184,197,207,223],"envision":[34],"simulators":[35],"simulation-based":[37],"digital":[38],"twins":[39],"becoming":[40],"primary":[41],"decision-making":[42],"tools.":[43],"ecosystems":[45,132,158,216,235],"leverage":[46],"many":[47],"heterogeneous":[48],"components,":[49],"making":[50],"simulation":[51,58,146],"a":[52,66,77,91,113,126,177,237],"non-trivial,":[53],"yet":[54],"critical":[55],"operation.":[56],"The":[57],"challenge":[59],"is":[60],"exacerbated":[61],"absence":[64],"comprehensive":[67],"reference":[68,92,127,139],"architecture":[69,128],"ecosystems;":[72],"lack":[74],"such":[76],"conceptual":[78],"model":[79],"can":[80],"be":[81],"costly":[82],"could":[84,99],"misguide":[85],"designers":[87],"engineers.":[89],"Without":[90],"architecture,":[93,140],"even":[94],"most":[96],"experienced":[97],"stakeholders":[98],"tinker":[100],"in":[101,193,236],"researching,":[102],"engineering,":[103],"or":[104],"maintaining":[105],"ecosystems.":[107],"In":[108],"this":[109],"work,":[110],"bring":[112],"three-fold":[114],"contribution":[115],"to":[116,137,149,232],"scientific":[118],"community.":[119],"Firstly,":[120],"synthesize,":[122],"propose,":[123],"validate":[125],"(RA)":[129],"under":[133,159,217],"inference.":[134],"Then,":[135],"adhering":[136],"Kavier,":[143],"first":[145],"instrument":[147],"able":[148],"predict":[150,233],"efficiency":[155,213],"inference,":[160],"through":[161],"discrete-event":[162],"cache-aware":[164],"simulation,":[165],"focusing":[166],"on":[167],"Key-Value-(KV-)Caching":[168],"prompt":[170],"prefix":[171,219],"caching":[172,220],"policies.":[173,221],"Through":[174],"experiments":[175],"with":[176],"Kavier":[178,189,226],"prototype":[179],"real-world":[181],"traces,":[182],"(i)":[183],"measure":[185],"accuracy":[187],"its":[191],"performance":[192,200],"massive-scale":[194],"simulations,":[195],"(ii)":[196],"compare":[198],"different":[202],"KV-Caching":[203],"policies,":[204],"(iii)":[206],"analyze":[208],"various":[218],"Overall,":[222],"show":[224],"that":[225],"enables":[227],"operators,":[228],"researchers,":[229],"engineers":[231],"time,":[238],"cost-efficient":[241],"way.":[242]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-27T00:00:00"}