{"id":"https://openalex.org/W7134948060","doi":"https://doi.org/10.48550/arxiv.2603.08721","title":"KernelCraft: Benchmarking for Agentic Close-to-Metal Kernel Generation on Emerging Hardware","display_name":"KernelCraft: Benchmarking for Agentic Close-to-Metal Kernel Generation on Emerging Hardware","publication_year":2026,"publication_date":"2026-02-10","ids":{"openalex":"https://openalex.org/W7134948060","doi":"https://doi.org/10.48550/arxiv.2603.08721"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.08721","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.08721","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.2603.08721","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124271622","display_name":"Jiayi Nie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nie, Jiayi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128783811","display_name":"Haoran Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Haoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124242411","display_name":"Yao Lai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lai, Yao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128745216","display_name":"Zeyu Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Zeyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128700969","display_name":"Cheng Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060393103","display_name":"Binglei Lou","orcid":"https://orcid.org/0000-0003-4662-1892"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lou, Binglei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013225839","display_name":"Erwei Wang","orcid":"https://orcid.org/0000-0002-3603-6852"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Erwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060302344","display_name":"Jianyi Cheng","orcid":"https://orcid.org/0000-0003-2791-2555"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Jianyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047443783","display_name":"Timothy M. Jones","orcid":"https://orcid.org/0000-0002-4114-7661"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jones, Timothy M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128790245","display_name":"Robert Mullins","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mullins, Robert","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009099496","display_name":"Rika Antonova","orcid":"https://orcid.org/0000-0002-3018-2445"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Antonova, Rika","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128716097","display_name":"Yiren Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Yiren","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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.5860999822616577,"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":0.5860999822616577,"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/T10456","display_name":"Multi-Agent Systems and Negotiation","score":0.03620000183582306,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.03400000184774399,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6922000050544739},{"id":"https://openalex.org/keywords/compiler","display_name":"Compiler","score":0.6521000266075134},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6478999853134155},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6442000269889832},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5766000151634216},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.570900022983551},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.48730000853538513},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4629000127315521}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7822999954223633},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6922000050544739},{"id":"https://openalex.org/C169590947","wikidata":"https://www.wikidata.org/wiki/Q47506","display_name":"Compiler","level":2,"score":0.6521000266075134},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6478999853134155},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6442000269889832},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5766000151634216},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.570900022983551},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48730000853538513},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4629000127315521},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.4106999933719635},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3952000141143799},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.3400999903678894},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.32580000162124634},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2992999851703644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2980000078678131},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.2964000105857849},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.2854999899864197},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2831000089645386},{"id":"https://openalex.org/C133162039","wikidata":"https://www.wikidata.org/wiki/Q1061077","display_name":"Code generation","level":3,"score":0.27880001068115234},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.27469998598098755},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.27079999446868896},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.2687999904155731},{"id":"https://openalex.org/C202491316","wikidata":"https://www.wikidata.org/wiki/Q272683","display_name":"Instruction set","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.25440001487731934},{"id":"https://openalex.org/C34972735","wikidata":"https://www.wikidata.org/wiki/Q2920267","display_name":"Engineering design process","level":2,"score":0.2524999976158142},{"id":"https://openalex.org/C2777062904","wikidata":"https://www.wikidata.org/wiki/Q545406","display_name":"Toolchain","level":3,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.08721","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.08721","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.2603.08721","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.08721","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"New":[0],"AI":[1],"accelerators":[2,90,103],"with":[3,67,111],"novel":[4],"instruction":[5],"set":[6],"architectures":[7],"(ISAs)":[8],"often":[9],"require":[10],"developers":[11],"to":[12,82,151],"manually":[13],"craft":[14],"low-level":[15,86],"kernels,":[16],"a":[17,92,132],"time-consuming":[18],"and":[19,61,84,136],"error-prone":[20],"process":[21],"that":[22,140],"does":[23],"not":[24],"scale":[25],"across":[26,100],"hardware":[27,32,66],"targets.":[28],"This":[29],"delays":[30],"emerging":[31,65,102],"platforms":[33],"from":[34],"reaching":[35],"the":[36,73,121,153],"market.":[37],"While":[38],"prior":[39],"LLM-based":[40],"code":[41],"generation":[42],"has":[43],"shown":[44],"promise":[45],"in":[46],"mature":[47],"GPU":[48],"ecosystems,":[49],"it":[50],"remains":[51],"unclear":[52],"whether":[53],"agentic":[54],"LLM":[55,79],"systems":[56],"can":[57],"quickly":[58],"produce":[59,137],"valid":[60],"efficient":[62],"kernels":[63,87,127,139],"for":[64,76,88,128],"new":[68],"ISAs.":[69],"We":[70,96],"present":[71],"KernelCraft:":[72],"first":[74],"benchmark":[75],"evaluating":[77],"an":[78],"agent's":[80],"ability":[81],"generate":[83,124],"optimize":[85],"customized":[89],"through":[91],"function-calling,":[93],"feedback-driven":[94],"workflow.":[95],"evaluate":[97],"agent":[98],"performance":[99],"three":[101],"on":[104],"more":[105],"than":[106],"20":[107],"machine-learning":[108],"tasks,":[109],"each":[110],"five":[112],"diverse":[113],"task":[114],"configurations.":[115],"Across":[116],"four":[117],"leading":[118],"reasoning":[119],"models,":[120],"strongest":[122],"agents":[123],"functionally":[125],"correct":[126],"unseen":[129],"ISAs":[130],"within":[131],"few":[133],"refinement":[134],"steps":[135],"optimized":[138],"match":[141],"or":[142],"outperform":[143],"compiler":[144],"baselines.":[145],"These":[146],"results":[147],"demonstrate":[148],"KernelCraft's":[149],"potential":[150],"accelerate":[152],"accelerator":[154],"chip":[155],"development":[156],"cycle.":[157],"KernelCraft":[158],"is":[159],"available":[160],"at":[161],"https://kernelcraft-cam.github.io/.":[162]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-12T00:00:00"}
