{"id":"https://openalex.org/W7171945520","doi":"https://doi.org/10.1145/3828820.3828825","title":"HORATIO: Bridging Management and Analysis of Traces at Scale","display_name":"HORATIO: Bridging Management and Analysis of Traces at Scale","publication_year":2026,"publication_date":"2026-07-31","ids":{"openalex":"https://openalex.org/W7171945520","doi":"https://doi.org/10.1145/3828820.3828825"},"language":null,"primary_location":{"id":"doi:10.1145/3828820.3828825","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3828820.3828825","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 38th International Conference on Scalable Scientific Data Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090459054","display_name":"Ray A. O. Sinurat","orcid":"https://orcid.org/0000-0002-7255-7647"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ray A. O. Sinurat","raw_affiliation_strings":["Department of Computer Science, University of Chicago, Chicago, Illinois, USA"],"raw_orcid":"https://orcid.org/0000-0002-7255-7647","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Chicago, Chicago, Illinois, USA","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140481772","display_name":"William Nixon","orcid":"https://orcid.org/0009-0005-7585-9076"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William Nixon","raw_affiliation_strings":["Department of Computer Science, University of Chicago, Chicago, Illinois, USA"],"raw_orcid":"https://orcid.org/0009-0005-7585-9076","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Chicago, Chicago, Illinois, USA","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085438892","display_name":"Haryadi S. Gunawi","orcid":"https://orcid.org/0000-0003-3680-8450"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haryadi S. Gunawi","raw_affiliation_strings":["Department of Computer Science, University of Chicago, Chicago, Illinois, USA"],"raw_orcid":"https://orcid.org/0000-0003-3680-8450","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Chicago, Chicago, Illinois, USA","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066306669","display_name":"Nikoli Dryden","orcid":null},"institutions":[{"id":"https://openalex.org/I1282311441","display_name":"Lawrence Livermore National Laboratory","ror":"https://ror.org/041nk4h53","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282311441","https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210138311"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nikoli Dryden","raw_affiliation_strings":["Lawrence Livermore National Laboratory, Livermore, California, USA"],"raw_orcid":"https://orcid.org/0000-0002-9965-3647","affiliations":[{"raw_affiliation_string":"Lawrence Livermore National Laboratory, Livermore, California, USA","institution_ids":["https://openalex.org/I1282311441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082476581","display_name":"Hariharan Devarajan","orcid":"https://orcid.org/0000-0001-5625-3494"},"institutions":[{"id":"https://openalex.org/I1282311441","display_name":"Lawrence Livermore National Laboratory","ror":"https://ror.org/041nk4h53","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282311441","https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210138311"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hariharan Devarajan","raw_affiliation_strings":["Lawrence Livermore National Laboratory, Livermore, California, USA"],"raw_orcid":"https://orcid.org/0000-0001-5625-3494","affiliations":[{"raw_affiliation_string":"Lawrence Livermore National Laboratory, Livermore, California, USA","institution_ids":["https://openalex.org/I1282311441"]}]}],"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":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.6913999915122986},{"id":"https://openalex.org/keywords/profiling","display_name":"Profiling (computer programming)","score":0.6097999811172485},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.5249999761581421},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5009999871253967},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.47999998927116394},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.4636000096797943},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.42969998717308044},{"id":"https://openalex.org/keywords/supercomputer","display_name":"Supercomputer","score":0.41499999165534973},{"id":"https://openalex.org/keywords/macro","display_name":"Macro","score":0.39730000495910645},{"id":"https://openalex.org/keywords/terabyte","display_name":"Terabyte","score":0.3865000009536743}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8029999732971191},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6913999915122986},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.6097999811172485},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5249999761581421},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5009999871253967},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.47999998927116394},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.4636000096797943},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.42969998717308044},{"id":"https://openalex.org/C83283714","wikidata":"https://www.wikidata.org/wiki/Q121117","display_name":"Supercomputer","level":2,"score":0.41499999165534973},{"id":"https://openalex.org/C166955791","wikidata":"https://www.wikidata.org/wiki/Q629579","display_name":"Macro","level":2,"score":0.39730000495910645},{"id":"https://openalex.org/C199683683","wikidata":"https://www.wikidata.org/wiki/Q8799","display_name":"Terabyte","level":2,"score":0.3865000009536743},{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.38199999928474426},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.3555000126361847},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.3456000089645386},{"id":"https://openalex.org/C13600138","wikidata":"https://www.wikidata.org/wiki/Q8799","display_name":"Petabyte","level":3,"score":0.3384000062942505},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3357999920845032},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3278000056743622},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.32760000228881836},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.32109999656677246},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.3149000108242035},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.2978000044822693},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C147224247","wikidata":"https://www.wikidata.org/wiki/Q885373","display_name":"Bloom filter","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C1668388","wikidata":"https://www.wikidata.org/wiki/Q1149776","display_name":"Data management","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C13424479","wikidata":"https://www.wikidata.org/wiki/Q5687237","display_name":"Haystack","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.25870001316070557},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.25839999318122864},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.25760000944137573},{"id":"https://openalex.org/C6385141","wikidata":"https://www.wikidata.org/wiki/Q5170558","display_name":"Coring","level":3,"score":0.25609999895095825},{"id":"https://openalex.org/C78168278","wikidata":"https://www.wikidata.org/wiki/Q5227269","display_name":"Data cube","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2547000050544739},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3828820.3828825","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3828820.3828825","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 38th International Conference on Scalable Scientific Data Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5185311795","display_name":"PPoSS: Planning: CP2: Towards Systems Correctness Checkability and Performance Predictability at Scale","funder_award_id":"2028427","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W25727798","https://openalex.org/W1545880915","https://openalex.org/W2104680817","https://openalex.org/W2125763460","https://openalex.org/W2144463710","https://openalex.org/W2157692945","https://openalex.org/W2971243175","https://openalex.org/W3025935268","https://openalex.org/W3046624992","https://openalex.org/W3094428287","https://openalex.org/W3173397016","https://openalex.org/W3207452942","https://openalex.org/W4206038948","https://openalex.org/W4287394385","https://openalex.org/W4288350939","https://openalex.org/W4299455392","https://openalex.org/W4322718191","https://openalex.org/W4385623118","https://openalex.org/W4394656104","https://openalex.org/W4405755678","https://openalex.org/W4413411846"],"related_works":[],"abstract_inverted_index":{"Modern":[0],"scientific":[1,223,252],"and":[2,12,17,38,62,96,117,147,222,225,251,285],"deep":[3],"learning":[4],"workloads":[5],"on":[6,10,230,246,280,293],"HPC":[7],"systems":[8],"rely":[9],"profiling":[11,68],"tracing":[13],"across":[14,219],"multiple":[15],"software":[16],"hardware":[18],"layers,":[19],"generating":[20],"diagnostic":[21],"traces":[22,32,45,79,121],"that":[23,67,114,206,257],"often":[24,42],"reach":[25],"terabyte":[26],"scale.":[27,305],"Existing":[28],"approaches":[29],"manage":[30],"these":[31,103],"along":[33],"two":[34],"axes:":[35],"trace":[36,111,204],"formats":[37],"analysis":[39,93],"tooling.":[40],"Practitioners":[41],"convert":[43],"raw":[44,56,78,110,120,139,165],"into":[46],"queryable":[47],"formats,":[48],"but":[49,83],"doing":[50],"so":[51],"nearly":[52],"doubles":[53],"storage":[54],"when":[55],"files":[57],"are":[58],"retained":[59],"for":[60,191],"compatibility":[61],"requires":[63,85],"upfront":[64],"schema":[65],"discovery":[66],"tools":[69],"cannot":[70,259],"guarantee.":[71],"A":[72],"cleaner":[73],"path":[74,288],"is":[75],"to":[76,154,183,227,274],"make":[77],"efficient":[80],"in":[81],"place,":[82],"this":[84],"overcoming":[86],"three":[87],"limitations:":[88],"lack":[89,97],"of":[90,98],"selective":[91,151],"querying,":[92],"throughput":[94,172],"bottlenecks,":[95],"physical":[99],"clustering.":[100],"To":[101],"address":[102],"limitations":[104],"jointly,":[105],"we":[106],"developed":[107],"Horatio,":[108],"a":[109,132,184,213,265,294],"management":[112],"framework":[113],"indexes,":[115],"analyzes,":[116],"physically":[118],"clusters":[119],"directly.":[122],"Three":[123],"findings":[124],"emerge":[125],"from":[126],"our":[127],"work.":[128],"First,":[129],"Horatio":[130,254],"stores":[131],"lightweight":[133],"RocksDB-backed":[134],"auxiliary":[135],"index":[136],"alongside":[137],"the":[138,168,198,208,233,238,281],"trace,":[140,269],"including":[141],"gzip":[142],"checkpoints,":[143],"per-chunk":[144],"bloom":[145],"filters,":[146],"chunk-level":[148],"statistics,":[149],"delivering":[150],"queries":[152],"up":[153,226],"75":[155],"\u00d7":[156,164,195,216,229,276,292],"faster":[157],"than":[158],"naive":[159],"Parquet":[160],"at":[161,277,290,303],"\u223c":[162],"1.01":[163],"storage,":[166],"with":[167,237,242],"highest":[169],"cross-query":[170],"mean":[171],"(232":[173],"M":[174],"events/s)":[175],"among":[176],"state-of-the-art":[177],"formats.":[178],"Second,":[179],"offloading":[180],"event-level":[181],"computation":[182],"native":[185],"C++":[186],"backend":[187],"while":[188],"keeping":[189],"Dask":[190],"orchestration":[192],"yields":[193,212],"80\u201383":[194],"speedup":[196,218],"over":[197],"original":[199,243],"Dask-based":[200,287],"DFAnalyzer.":[201],"Third,":[202],"lossless":[203],"clustering":[205],"preserves":[207],"same":[209],"input":[210],"format":[211],"further":[214],"1.8\u20135.5":[215],"end-to-end":[217],"four":[220],"AI":[221,250],"workloads,":[224,253],"230":[228],"h5bench":[231],"where":[232,299],"preset":[234],"aligns":[235],"tightly":[236],"cluster":[239],"boundary,":[240],"all":[241],"layouts":[244],"reconstructible":[245],"demand.":[247],"Across":[248],"five":[249],"completes":[255],"pipelines":[256],"DFAnalyzer":[258,300],"finish":[260],"within":[261],"8":[262],"hours.":[263],"On":[264],"2.2":[266],"TB":[267],"uncompressed":[268],"Horatio\u2019s":[270],"MPI-based":[271],"mode":[272],"scales":[273],"16":[275],"32":[278],"nodes":[279],"full":[282],"event":[283],"set":[284],"its":[286],"peaks":[289],"4":[291],"preset-filtered":[295],"workload,":[296],"both":[297],"completing":[298],"hits":[301],"OOM":[302],"every":[304]},"counts_by_year":[],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2026-08-01T00:00:00"}