{"id":"https://openalex.org/W7155096780","doi":"https://doi.org/10.48550/arxiv.2604.18529","title":"HybridGen: Efficient LLM Generative Inference via CPU-GPU Hybrid Computing","display_name":"HybridGen: Efficient LLM Generative Inference via CPU-GPU Hybrid Computing","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W7155096780","doi":"https://doi.org/10.48550/arxiv.2604.18529"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.18529","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18529","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.2604.18529","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134198282","display_name":"Mao Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Mao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134164791","display_name":"Xi Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064524083","display_name":"Guilherme Cox","orcid":"https://orcid.org/0000-0001-8292-4554"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cox, Guilherme","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134202931","display_name":"Dong Li","orcid":"https://orcid.org/0009-0009-6044-5101"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Dong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5081531196","display_name":"Hyeran Jeon","orcid":"https://orcid.org/0000-0002-1767-8198"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeon, Hyeran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.6434000134468079,"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":0.6434000134468079,"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/T11181","display_name":"Advanced Data Storage Technologies","score":0.16030000150203705,"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.04769999906420708,"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/cache","display_name":"Cache","score":0.7621999979019165},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.49959999322891235},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.47690001130104065},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4616999924182892},{"id":"https://openalex.org/keywords/cache-only-memory-architecture","display_name":"Cache-only memory architecture","score":0.4043999910354614},{"id":"https://openalex.org/keywords/cpu-cache","display_name":"CPU cache","score":0.3727000057697296},{"id":"https://openalex.org/keywords/cache-coloring","display_name":"Cache coloring","score":0.3659000098705292}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8402000069618225},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.7621999979019165},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5636000037193298},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.49959999322891235},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.47690001130104065},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4616999924182892},{"id":"https://openalex.org/C3720319","wikidata":"https://www.wikidata.org/wiki/Q5015937","display_name":"Cache-only memory architecture","level":5,"score":0.4043999910354614},{"id":"https://openalex.org/C189783530","wikidata":"https://www.wikidata.org/wiki/Q352090","display_name":"CPU cache","level":3,"score":0.3727000057697296},{"id":"https://openalex.org/C201148951","wikidata":"https://www.wikidata.org/wiki/Q5015976","display_name":"Cache coloring","level":4,"score":0.3659000098705292},{"id":"https://openalex.org/C176649486","wikidata":"https://www.wikidata.org/wiki/Q2308807","display_name":"Memory management","level":3,"score":0.34150001406669617},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.33000001311302185},{"id":"https://openalex.org/C113166858","wikidata":"https://www.wikidata.org/wiki/Q5015981","display_name":"Cache pollution","level":5,"score":0.3287000060081482},{"id":"https://openalex.org/C38556500","wikidata":"https://www.wikidata.org/wiki/Q13404475","display_name":"Cache algorithms","level":4,"score":0.31679999828338623},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.29899999499320984},{"id":"https://openalex.org/C49154492","wikidata":"https://www.wikidata.org/wiki/Q5300","display_name":"Central processing unit","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C12186640","wikidata":"https://www.wikidata.org/wiki/Q6815743","display_name":"Memory model","level":3,"score":0.28790000081062317},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2680000066757202},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.2606000006198883},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2597000002861023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2563999891281128},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25600001215934753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.18529","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18529","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.2604.18529","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18529","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"modern":[1],"LLMs":[2],"support":[3],"thousands":[4],"to":[5,12],"millions":[6],"of":[7,14,103],"tokens,":[8],"KV":[9,25,54,119,145],"caches":[10],"grow":[11],"hundreds":[13],"gigabytes,":[15],"stressing":[16],"memory":[17,52,79,138],"capacity":[18],"and":[19,28,46,99,117],"bandwidth.":[20],"Existing":[21],"solutions,":[22],"such":[23],"as":[24],"cache":[26,55,120,146],"pruning":[27],"offloading,":[29],"alleviate":[30],"these":[31,108],"but":[32],"underutilize":[33],"hardware":[34],"by":[35,109,149],"relying":[36],"solely":[37],"on":[38,74,131,151],"either":[39],"GPU":[40,133],"or":[41],"CPU":[42,50],"for":[43,53,65],"attention":[44,63,73,89,111],"computing,":[45],"considering":[47],"yet":[48],"limited":[49],"local":[51],"storage.":[56],"We":[57],"propose":[58],"HybridGen,":[59],"an":[60],"efficient":[61],"hybrid":[62],"framework":[64],"long-context":[66],"LLM":[67,125],"inference.":[68],"HybridGen":[69,106,141],"enables":[70],"CPU-GPU":[71,93],"collaborative":[72],"systems":[75],"with":[76,96,123,127,135],"expanded":[77],"tiered":[78,104],"(e.g.,":[80],"CXL":[81],"memory),":[82],"addressing":[83],"three":[84,124,132],"key":[85],"challenges:":[86],"(1)":[87],"multi-dimensional":[88],"dependencies,":[90],"(2)":[91],"intensifying":[92],"load":[94],"imbalance":[95],"longer":[97],"sequences,":[98],"(3)":[100],"NUMA":[101],"penalty":[102],"memories.":[105],"tackles":[107],"introducing":[110],"logit":[112],"parallelism,":[113],"a":[114,136],"feedback-driven":[115],"scheduler,":[116],"semantic-aware":[118],"mapping.":[121],"Experiments":[122],"models":[126],"eleven":[128],"different":[129],"sizes":[130],"platforms":[134],"CXL-expanded":[137],"show":[139],"that":[140],"outperforms":[142],"six":[143],"state-of-the-art":[144],"management":[147],"methods":[148],"1.41x--3.2x":[150],"average":[152],"while":[153],"maintaining":[154],"superior":[155],"accuracy.":[156]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-22T00:00:00"}