{"id":"https://openalex.org/W4287393709","doi":"https://doi.org/10.4230/lipics.ecrts.2026.17","title":"Uncertainty-Aware Resource Allocation for Multi-Path Programs with In-Kernel Predictions","display_name":"Uncertainty-Aware Resource Allocation for Multi-Path Programs with In-Kernel Predictions","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W4287393709","doi":"https://doi.org/10.4230/lipics.ecrts.2026.17"},"language":"en","primary_location":{"id":"pmh:doi:10.4230/lipics.ecrts.2026.17","is_oa":true,"landing_page_url":"https://github.com/phan-lab/MPORA","pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"ConferencePaper"},"type":"conference-paper","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://github.com/phan-lab/MPORA","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Eisenklam, Abigail","orcid":"https://orcid.org/0000-0001-7462-667X"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eisenklam, Abigail","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":"https://orcid.org/0000-0001-7462-667X","affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Montenegro G., Carlos A.","orcid":"https://orcid.org/0009-0004-5710-9039"},"institutions":[{"id":"https://openalex.org/I185103710","display_name":"University of California, Santa Cruz","ror":"https://ror.org/03s65by71","country_code":"US","type":"education","lineage":["https://openalex.org/I185103710"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Montenegro G., Carlos A.","raw_affiliation_strings":["University of California, Santa Cruz, CA, USA"],"raw_orcid":"https://orcid.org/0009-0004-5710-9039","affiliations":[{"raw_affiliation_string":"University of California, Santa Cruz, CA, USA","institution_ids":["https://openalex.org/I185103710"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wang, Xian","orcid":"https://orcid.org/0000-0002-7885-4618"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wang, Xian","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-7885-4618","affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Cai, Yifan","orcid":"https://orcid.org/0009-0003-8125-1054"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cai, Yifan","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":"https://orcid.org/0009-0003-8125-1054","affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Gifford, Robert","orcid":"https://orcid.org/0000-0003-2937-6215"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gifford, Robert","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":"https://orcid.org/0000-0003-2937-6215","affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Phan, Linh Thi Xuan","orcid":"https://orcid.org/0000-0002-3458-7511"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Phan, Linh Thi Xuan","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3458-7511","affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":null,"display_name":"Sanfelice, Ricardo G.","orcid":"https://orcid.org/0000-0002-6671-5362"},"institutions":[{"id":"https://openalex.org/I185103710","display_name":"University of California, Santa Cruz","ror":"https://ror.org/03s65by71","country_code":"US","type":"education","lineage":["https://openalex.org/I185103710"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanfelice, Ricardo G.","raw_affiliation_strings":["University of California, Santa Cruz, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-6671-5362","affiliations":[{"raw_affiliation_string":"University of California, Santa Cruz, CA, USA","institution_ids":["https://openalex.org/I185103710"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":74,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7256022691726685},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.694622814655304},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6489886045455933},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6327476501464844},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.6262703537940979},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5257003307342529},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48679348826408386},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.45843014121055603},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.41130876541137695},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.23600637912750244},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.16109547019004822}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7256022691726685},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.694622814655304},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6489886045455933},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6327476501464844},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6262703537940979},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5257003307342529},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48679348826408386},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.45843014121055603},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.41130876541137695},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.23600637912750244},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.16109547019004822},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.4230/lipics.ecrts.2026.17","is_oa":true,"landing_page_url":"https://github.com/phan-lab/MPORA","pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"ConferencePaper"},{"id":"doi:10.4230/lipics.ecrts.2026.17","is_oa":true,"landing_page_url":"https://doi.org/10.4230/lipics.ecrts.2026.17","pdf_url":null,"source":{"id":"https://openalex.org/S7407052059","display_name":"Dagstuhl Research Online Publication Server","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"ConferencePaper"}],"best_oa_location":{"id":"pmh:doi:10.4230/lipics.ecrts.2026.17","is_oa":true,"landing_page_url":"https://github.com/phan-lab/MPORA","pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"ConferencePaper"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8700000047683716,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W2766514146","https://openalex.org/W4289703016","https://openalex.org/W2885516856","https://openalex.org/W3094138326","https://openalex.org/W4310224730","https://openalex.org/W1799405941"],"abstract_inverted_index":{"Predictable":[0],"timing":[1],"on":[2,34,128],"multicore":[3,35],"systems":[4],"requires":[5],"careful":[6],"management":[7],"of":[8],"shared":[9],"resources":[10],"such":[11],"as":[12,41,117],"the":[13,107],"last-level":[14],"cache":[15],"and":[16,50,61,66,141,150],"memory":[17],"bandwidth.":[18],"This":[19],"paper":[20],"presents":[21],"MPORA,":[22],"an":[23],"uncertainty-aware":[24,111],"dynamic":[25],"resource":[26,87],"allocation":[27],"framework":[28],"for":[29],"multi-path,":[30],"input-dependent":[31],"real-time":[32],"tasks":[33],"platforms.":[36],"MPORA":[37,56,101,116,134],"models":[38,75],"each":[39],"job":[40,58,95],"a":[42,81,118],"discrete-time":[43],"dynamical":[44],"system":[45],"that":[46,89,133],"captures":[47],"execution":[48,59,68],"dynamics":[49],"resource-dependent":[51],"performance":[52],"indicators.":[53],"At":[54],"runtime,":[55],"monitors":[57],"states":[60],"predicts":[62],"short-term":[63],"instruction":[64],"rates":[65],"remaining":[67],"times":[69,152],"under":[70,138],"candidate":[71],"allocations":[72,88],"using":[73],"predictive":[74],"trained":[76],"offline.":[77],"It":[78],"then":[79],"solves":[80],"receding-horizon":[82],"optimization":[83,108],"problem":[84],"to":[85],"compute":[86],"maximize":[90],"system-wide":[91],"progress":[92],"while":[93,147],"meeting":[94],"deadlines.":[96],"To":[97],"address":[98],"prediction":[99,105],"uncertainty,":[100],"integrates":[102],"weighted":[103],"conformal":[104],"into":[106],"formulation,":[109],"enabling":[110],"deadline":[112],"constraints.":[113],"We":[114],"implement":[115],"Linux":[119],"kernel":[120],"module":[121],"with":[122,144],"microsecond-scale":[123],"inference":[124],"overhead.":[125],"Experimental":[126],"results":[127],"SPEC":[129],"CPU":[130],"benchmarks":[131],"show":[132],"delivers":[135],"accurate":[136],"predictions":[137],"unseen":[139],"inputs":[140],"distribution":[142],"shifts":[143],"low":[145],"overhead,":[146],"improving":[148],"schedulability":[149],"response":[151],"over":[153],"existing":[154],"methods.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":22},{"year":2023,"cited_by_count":30},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2022-07-25T00:00:00"}
