{"id":"https://openalex.org/W7166167986","doi":"https://doi.org/10.48550/arxiv.2606.26453","title":"Optimizing CUDA like a Human: Micro-Profiling Tools as Expert Surrogates for LLM-Based GPU Kernel Optimization","display_name":"Optimizing CUDA like a Human: Micro-Profiling Tools as Expert Surrogates for LLM-Based GPU Kernel Optimization","publication_year":2026,"publication_date":"2026-06-24","ids":{"openalex":"https://openalex.org/W7166167986","doi":"https://doi.org/10.48550/arxiv.2606.26453"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.26453","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.26453","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.2606.26453","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024224392","display_name":"Jiading Gai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gai, Jiading","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139406717","display_name":"Shuai Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Shuai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050663933","display_name":"Kaj Bostrom","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bostrom, Kaj","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006022044","display_name":"J W Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Jin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005457523","display_name":"Vihang Patil","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Patil, Vihang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139408060","display_name":"Haoyang Fang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang, Haoyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139410743","display_name":"Bernie Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Bernie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139457576","display_name":"Huzefa Rangwala","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rangwala, Huzefa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5110359290","display_name":"George Karypis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karypis, George","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":0.6460999846458435,"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":0.6460999846458435,"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":0.18610000610351562,"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/T14347","display_name":"Big Data and Digital Economy","score":0.03720000013709068,"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/bottleneck","display_name":"Bottleneck","score":0.6158999800682068},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5626999735832214},{"id":"https://openalex.org/keywords/cuda","display_name":"CUDA","score":0.5397999882698059},{"id":"https://openalex.org/keywords/code-generation","display_name":"Code generation","score":0.45080000162124634},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4415999948978424},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4147000014781952}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8222000002861023},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6158999800682068},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5626999735832214},{"id":"https://openalex.org/C2778119891","wikidata":"https://www.wikidata.org/wiki/Q477690","display_name":"CUDA","level":2,"score":0.5397999882698059},{"id":"https://openalex.org/C133162039","wikidata":"https://www.wikidata.org/wiki/Q1061077","display_name":"Code generation","level":3,"score":0.45080000162124634},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4415999948978424},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4147000014781952},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4142000079154968},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.4124999940395355},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.3984000086784363},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.382999986410141},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3560999929904938},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.29190000891685486},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C199168358","wikidata":"https://www.wikidata.org/wiki/Q3367000","display_name":"Orchestration","level":3,"score":0.27140000462532043},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.26453","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.26453","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.2606.26453","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.26453","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":[{"id":"https://metadata.un.org/sdg/7","score":0.8621209263801575,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"present":[1],"KernelPro,":[2],"a":[3,39,61,86,152],"closed-loop":[4],"multi-agent":[5],"system":[6],"that":[7,43,161],"automatically":[8],"generates,":[9],"profiles,":[10],"and":[11,29,81,98,104,166,190],"iteratively":[12],"optimizes":[13],"GPU":[14],"kernel":[15,205],"code":[16,23,109,113],"by":[17,150],"integrating":[18],"large":[19],"language":[20,58],"model":[21],"(LLM)":[22],"generation":[24,110],"with":[25,89],"hardware":[26,53],"profiler":[27],"feedback":[28,41],"pluggable":[30,48],"bottleneck":[31,68],"detection":[32],"tools.":[33],"KernelPro":[34,121,144,200],"introduces":[35],"four":[36],"contributions:":[37],"(1)":[38],"semantic":[40],"operator":[42],"encodes":[44],"expert":[45],"heuristics":[46],"as":[47],"micro-profiling":[49,171],"tools,":[50],"transforming":[51],"raw":[52,177],"metrics":[54],"into":[55],"actionable":[56],"natural":[57],"guidance;":[59],"(2)":[60],"two-stage":[62],"tool":[63,192],"invocation":[64],"architecture":[65],"where":[66],"roofline-based":[67],"classification":[69],"filters":[70],"which":[71],"specialized":[72],"analysis":[73],"tools":[74,172],"execute,":[75],"combining":[76],"kernel-level":[77],"(ncu),":[78],"instruction-level":[79],"(SASS),":[80],"system-level":[82],"(nsys)":[83],"profiling;":[84],"(3)":[85],"domain-adapted":[87],"MCTS":[88,179],"progressive":[90],"widening,":[91],"asymmetric":[92],"branching,":[93],"log-reward":[94],"calibration,":[95],"dead-end":[96],"pruning,":[97],"search":[99,114,180],"memory":[100],"for":[101],"cross-iteration":[102],"learning;":[103],"(4)":[105],"direct":[106],"CuTe":[107],"source-level":[108],"via":[111],"autonomous":[112],"over":[115,147],"the":[116,202,213],"CUTLASS/CuTe":[117],"codebase.":[118],"On":[119,138],"KernelBench,":[120],"achieves":[122,145],"geometric":[123,183],"mean":[124,184],"speedups":[125],"of":[126,216],"2.42x/4.69x/5.30x":[127],"on":[128],"Levels":[129],"1/2/3,":[130],"establishing":[131],"state-of-the-art":[132],"performance":[133],"across":[134],"all":[135],"difficulty":[136],"levels.":[137],"VeOmni's":[139],"expert-optimized":[140],"MoE":[141],"training":[142],"kernels,":[143],"1.23x":[146],"hand-tuned":[148],"Triton":[149],"generating":[151],"from-scratch":[153],"raw-CUDA+CuTe":[154],"Hopper":[155],"WGMMA":[156],"kernel.":[157],"Ablation":[158],"studies":[159],"demonstrate":[160],"each":[162],"design":[163],"component":[164],"independently":[165],"significantly":[167],"improves":[168],"optimization":[169],"quality:":[170],"(p":[173],"&lt;":[174],"0.0001":[175],"vs":[176,185],"metrics),":[178],"(26%":[181],"higher":[182],"greedy,":[186],"p":[187,196],"=":[188,197],"0.004),":[189],"proactive":[191],"orchestration":[193],"(23%":[194],"improvement,":[195],"0.035).":[198],"Finally,":[199],"is":[201],"first":[203],"CUDA":[204],"coding":[206],"agent":[207],"to":[208],"optimize":[209],"energy":[210,223],"efficiency":[211],"beyond":[212],"speed-only":[214],"focus":[215],"prior":[217],"systems,":[218],"demonstrating":[219],"an":[220],"11.6%":[221],"measured":[222],"reduction":[224],"at":[225],"matched":[226],"speed.":[227]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-27T00:00:00"}
