{"id":"https://openalex.org/W4404400711","doi":"https://doi.org/10.1145/3694715.3695970","title":"Reducing Energy Bloat in Large Model Training","display_name":"Reducing Energy Bloat in Large Model Training","publication_year":2024,"publication_date":"2024-11-04","ids":{"openalex":"https://openalex.org/W4404400711","doi":"https://doi.org/10.1145/3694715.3695970"},"language":"en","primary_location":{"id":"doi:10.1145/3694715.3695970","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3694715.3695970","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3694715.3695970","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM SIGOPS 30th Symposium on Operating Systems Principles","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3694715.3695970","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016566636","display_name":"Jae-Won Chung","orcid":"https://orcid.org/0000-0001-5924-3427"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jae-Won Chung","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, United States"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, United States","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102591922","display_name":"Yile Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yile Gu","raw_affiliation_strings":["University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064139539","display_name":"Insu Jang","orcid":"https://orcid.org/0009-0007-5206-2333"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Insu Jang","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013741856","display_name":"Luoxi Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Luoxi Meng","raw_affiliation_strings":["University of California, San Diego, San Diego, CA, United States"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego, San Diego, CA, United States","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008689083","display_name":"Nikhil Bansal","orcid":"https://orcid.org/0000-0002-6290-0894"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nikhil Bansal","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, United States"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, United States","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013180923","display_name":"Mosharaf Chowdhury","orcid":"https://orcid.org/0000-0003-0884-6740"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mosharaf Chowdhury","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, United States"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, United States","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5016566636"],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":2.4928,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.90838593,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"144","last_page":"159"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9988999962806702,"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.9972000122070312,"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/training","display_name":"Training (meteorology)","score":0.7091177105903625},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5630419850349426},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.5203744769096375},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0869709849357605},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.08619064092636108},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07737922668457031},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07625138759613037}],"concepts":[{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.7091177105903625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5630419850349426},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5203744769096375},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0869709849357605},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.08619064092636108},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07737922668457031},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07625138759613037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3694715.3695970","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3694715.3695970","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3694715.3695970","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM SIGOPS 30th Symposium on Operating Systems Principles","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3694715.3695970","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3694715.3695970","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3694715.3695970","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM SIGOPS 30th Symposium on Operating Systems Principles","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8700000047683716,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G3434055629","display_name":null,"funder_award_id":"CNS-2104243","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4983037987","display_name":null,"funder_award_id":"CCF-2327011","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8061712885","display_name":null,"funder_award_id":"CNS-2106184","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":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4404400711.pdf"},"referenced_works_count":67,"referenced_works":["https://openalex.org/W2020828423","https://openalex.org/W2041242446","https://openalex.org/W2057087550","https://openalex.org/W2149342630","https://openalex.org/W2266856261","https://openalex.org/W2289252105","https://openalex.org/W2290287050","https://openalex.org/W2338908902","https://openalex.org/W2523060838","https://openalex.org/W2604319603","https://openalex.org/W2743649614","https://openalex.org/W2767346922","https://openalex.org/W2896457183","https://openalex.org/W2901299405","https://openalex.org/W2910100551","https://openalex.org/W2913104037","https://openalex.org/W2922092846","https://openalex.org/W2963809228","https://openalex.org/W2964137095","https://openalex.org/W2969388332","https://openalex.org/W2970971581","https://openalex.org/W2979826702","https://openalex.org/W2981852735","https://openalex.org/W3010927549","https://openalex.org/W3024745949","https://openalex.org/W3033527233","https://openalex.org/W3036879053","https://openalex.org/W3038581078","https://openalex.org/W3042358861","https://openalex.org/W3043154389","https://openalex.org/W3043413334","https://openalex.org/W3094850318","https://openalex.org/W3118922386","https://openalex.org/W3141123509","https://openalex.org/W3169545043","https://openalex.org/W3204998121","https://openalex.org/W3214897310","https://openalex.org/W4205348240","https://openalex.org/W4221167110","https://openalex.org/W4225004481","https://openalex.org/W4226479682","https://openalex.org/W4244424643","https://openalex.org/W4283157527","https://openalex.org/W4288089799","https://openalex.org/W4291961336","https://openalex.org/W4308245305","https://openalex.org/W4308426193","https://openalex.org/W4310285541","https://openalex.org/W4323557219","https://openalex.org/W4327694855","https://openalex.org/W4362469997","https://openalex.org/W4377235369","https://openalex.org/W4386840193","https://openalex.org/W4387303318","https://openalex.org/W4392223539","https://openalex.org/W4394871754","https://openalex.org/W4395106452","https://openalex.org/W4399147211","https://openalex.org/W4400909964","https://openalex.org/W4401699727","https://openalex.org/W4402475836","https://openalex.org/W6703652217","https://openalex.org/W6739901393","https://openalex.org/W6778883912","https://openalex.org/W6780373310","https://openalex.org/W6894204878","https://openalex.org/W7067822191"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W230091440","https://openalex.org/W2390279801","https://openalex.org/W2233261550","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2810751659"],"abstract_inverted_index":{"Training":[0],"large":[1],"AI":[2,28],"models":[3],"on":[4],"numerous":[5],"GPUs":[6],"consumes":[7],"a":[8,45],"massive":[9],"amount":[10],"of":[11,17],"energy,":[12],"making":[13],"power":[14],"delivery":[15],"one":[16],"the":[18],"largest":[19],"limiting":[20],"factors":[21],"in":[22],"building":[23],"and":[24],"operating":[25],"datacenters":[26],"for":[27],"workloads.":[29],"However,":[30],"we":[31],"observe":[32],"that":[33],"not":[34],"all":[35],"energy":[36,59],"consumed":[37],"during":[38],"training":[39],"directly":[40],"contributes":[41],"to":[42],"end-to-end":[43],"throughput;":[44],"significant":[46],"portion":[47,58],"can":[48],"be":[49],"removed":[50],"without":[51],"slowing":[52],"down":[53],"training.":[54],"We":[55],"call":[56],"this":[57],"bloat.":[60]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
