{"id":"https://openalex.org/W3193985311","doi":"https://doi.org/10.1145/3503222.3507778","title":"Breaking the computation and communication abstraction barrier in distributed machine learning workloads","display_name":"Breaking the computation and communication abstraction barrier in distributed machine learning workloads","publication_year":2022,"publication_date":"2022-02-22","ids":{"openalex":"https://openalex.org/W3193985311","doi":"https://doi.org/10.1145/3503222.3507778","mag":"3193985311"},"language":"en","primary_location":{"id":"doi:10.1145/3503222.3507778","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503222.3507778","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems","raw_type":"proceedings-article"},"type":"preprint","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/A5034240415","display_name":"Abhinav Jangda","orcid":"https://orcid.org/0000-0002-4849-6776"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abhinav Jangda","raw_affiliation_strings":["University of Massachusetts at Amherst, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts at Amherst, USA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108705811","display_name":"Jun Huang","orcid":"https://orcid.org/0000-0003-4939-3880"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Huang","raw_affiliation_strings":["Ohio State University, USA"],"affiliations":[{"raw_affiliation_string":"Ohio State University, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100346586","display_name":"Ye Liu","orcid":"https://orcid.org/0000-0003-3273-8459"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guodong Liu","raw_affiliation_strings":["Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085729926","display_name":"Amir Hossein Nodehi Sabet","orcid":null},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amir Hossein Nodehi Sabet","raw_affiliation_strings":["University of California at Riverside, USA"],"affiliations":[{"raw_affiliation_string":"University of California at Riverside, USA","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077514991","display_name":"Saeed Maleki","orcid":"https://orcid.org/0000-0003-1107-1827"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saeed Maleki","raw_affiliation_strings":["Microsoft Research, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075076538","display_name":"Youshan Miao","orcid":"https://orcid.org/0000-0002-2395-9965"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youshan Miao","raw_affiliation_strings":["Microsoft Research, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040009052","display_name":"Madanlal Musuvathi","orcid":"https://orcid.org/0000-0002-2482-7892"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Madanlal Musuvathi","raw_affiliation_strings":["Microsoft Research, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013212213","display_name":"Todd Mytkowicz","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Todd Mytkowicz","raw_affiliation_strings":["Microsoft Research, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001454502","display_name":"Olli Saarikivi","orcid":"https://orcid.org/0000-0001-7596-4734"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Olli Saarikivi","raw_affiliation_strings":["Microsoft Research, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5034240415"],"corresponding_institution_ids":["https://openalex.org/I24603500"],"apc_list":null,"apc_paid":null,"fwci":6.4793,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.97032629,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"402","last_page":"416"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9987000226974487,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9980999827384949,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9973000288009644,"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/computer-science","display_name":"Computer science","score":0.8814160823822021},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.7584028244018555},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.7290695905685425},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.611771821975708},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5337563157081604},{"id":"https://openalex.org/keywords/abstraction-layer","display_name":"Abstraction layer","score":0.49349963665008545},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40292108058929443},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.344748854637146},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.14331987500190735},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.119803786277771}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8814160823822021},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.7584028244018555},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.7290695905685425},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.611771821975708},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5337563157081604},{"id":"https://openalex.org/C147358964","wikidata":"https://www.wikidata.org/wiki/Q1200992","display_name":"Abstraction layer","level":3,"score":0.49349963665008545},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40292108058929443},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.344748854637146},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.14331987500190735},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.119803786277771},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3503222.3507778","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503222.3507778","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.4099999964237213,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G5819448462","display_name":null,"funder_award_id":"CCF-2052696","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":45,"referenced_works":["https://openalex.org/W1493774699","https://openalex.org/W1522301498","https://openalex.org/W2026024102","https://openalex.org/W2055312318","https://openalex.org/W2063400505","https://openalex.org/W2076517649","https://openalex.org/W2163605009","https://openalex.org/W2163950090","https://openalex.org/W2173839706","https://openalex.org/W2340879669","https://openalex.org/W2419192351","https://openalex.org/W2550963337","https://openalex.org/W2557367833","https://openalex.org/W2594730095","https://openalex.org/W2608177516","https://openalex.org/W2612249218","https://openalex.org/W2753515784","https://openalex.org/W2772612468","https://openalex.org/W2804032941","https://openalex.org/W2914209329","https://openalex.org/W2948223045","https://openalex.org/W2963341956","https://openalex.org/W2963351145","https://openalex.org/W2963809228","https://openalex.org/W2969388332","https://openalex.org/W2970971581","https://openalex.org/W2973727699","https://openalex.org/W2991040477","https://openalex.org/W2995435108","https://openalex.org/W3037585619","https://openalex.org/W3037847693","https://openalex.org/W3040573126","https://openalex.org/W3086105743","https://openalex.org/W3090425474","https://openalex.org/W3090487264","https://openalex.org/W3096403968","https://openalex.org/W3098903812","https://openalex.org/W3129831491","https://openalex.org/W3132357455","https://openalex.org/W3153553004","https://openalex.org/W3188065709","https://openalex.org/W3188270315","https://openalex.org/W3204998121","https://openalex.org/W4240382083","https://openalex.org/W6958137753"],"related_works":["https://openalex.org/W1984744919","https://openalex.org/W2132930690","https://openalex.org/W2770599040","https://openalex.org/W1901380330","https://openalex.org/W3009812692","https://openalex.org/W2901324294","https://openalex.org/W4248324254","https://openalex.org/W3017219868","https://openalex.org/W2075164989","https://openalex.org/W3117872823"],"abstract_inverted_index":{"Recent":[0],"trends":[1],"towards":[2],"large":[3],"machine":[4,49],"learning":[5,50],"models":[6],"require":[7],"both":[8,90],"training":[9,21],"and":[10,32,45,82,93],"inference":[11],"tasks":[12],"to":[13,27,34,65],"be":[14],"distributed.":[15],"Considering":[16],"the":[17,39,67,79],"huge":[18],"cost":[19],"of":[20,69],"these":[22,75],"models,":[23],"it":[24],"is":[25,89],"imperative":[26],"unlock":[28],"optimizations":[29,64,76],"in":[30,48],"computation":[31,44,81],"communication":[33,46,83],"obtain":[35],"best":[36],"performance.":[37],"However,":[38,72],"current":[40],"logical":[41],"separation":[42],"between":[43],"kernels":[47],"frameworks":[51],"misses":[52],"optimization":[53],"opportunities":[54],"across":[55],"this":[56,59],"barrier.":[57],"Breaking":[58],"abstraction":[60],"can":[61],"provide":[62],"many":[63],"improve":[66],"performance":[68],"distributed":[70],"workloads.":[71],"manually":[73],"applying":[74],"requires":[77],"modifying":[78],"underlying":[80],"libraries":[84],"for":[85],"each":[86],"scenario,":[87],"which":[88],"time":[91],"consuming":[92],"error-prone.":[94]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}