{"id":"https://openalex.org/W3201621211","doi":"https://doi.org/10.1145/3460231.3474246","title":"cDLRM: Look Ahead Caching for Scalable Training of Recommendation Models","display_name":"cDLRM: Look Ahead Caching for Scalable Training of Recommendation Models","publication_year":2021,"publication_date":"2021-09-13","ids":{"openalex":"https://openalex.org/W3201621211","doi":"https://doi.org/10.1145/3460231.3474246","mag":"3201621211"},"language":"en","primary_location":{"id":"doi:10.1145/3460231.3474246","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3460231.3474246","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3460231.3474246","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifteenth ACM Conference on Recommender Systems","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/10.1145/3460231.3474246","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054449875","display_name":"Keshav Balasubramanian","orcid":null},"institutions":[{"id":"https://openalex.org/I2800817003","display_name":"Southern California University for Professional Studies","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]},{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Keshav Balasubramanian","raw_affiliation_strings":["SCIP University of Southern California, United States"],"affiliations":[{"raw_affiliation_string":"SCIP University of Southern California, United States","institution_ids":["https://openalex.org/I2800817003","https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007990050","display_name":"Abdulla Alshabanah","orcid":"https://orcid.org/0009-0009-7619-874X"},"institutions":[{"id":"https://openalex.org/I2800817003","display_name":"Southern California University for Professional Studies","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]},{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abdulla Alshabanah","raw_affiliation_strings":["SCIP University of Southern California, United States"],"affiliations":[{"raw_affiliation_string":"SCIP University of Southern California, United States","institution_ids":["https://openalex.org/I2800817003","https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021412883","display_name":"Joshua D Choe","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"Southern California University for Professional Studies","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joshua D Choe","raw_affiliation_strings":["SCIP University of Southern California, United States"],"affiliations":[{"raw_affiliation_string":"SCIP University of Southern California, United States","institution_ids":["https://openalex.org/I2800817003","https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018033573","display_name":"Murali Annavaram","orcid":"https://orcid.org/0000-0002-4633-6867"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"Southern California University for Professional Studies","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Murali Annavaram","raw_affiliation_strings":["SCIP University of Southern California, United States"],"affiliations":[{"raw_affiliation_string":"SCIP University of Southern California, United States","institution_ids":["https://openalex.org/I2800817003","https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5054449875"],"corresponding_institution_ids":["https://openalex.org/I1174212","https://openalex.org/I2800817003"],"apc_list":null,"apc_paid":null,"fwci":3.687,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.93822963,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"263","last_page":"272"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T11478","display_name":"Caching and Content Delivery","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.989300012588501,"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":0.8838690519332886},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7914614677429199},{"id":"https://openalex.org/keywords/instruction-prefetch","display_name":"Instruction prefetch","score":0.730525016784668},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6713480949401855},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.5972211360931396},{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.5670281648635864},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.5596214532852173},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.47256866097450256},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.46770355105400085},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.364014208316803},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31130725145339966},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2971840500831604},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.18439963459968567}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8838690519332886},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7914614677429199},{"id":"https://openalex.org/C133588205","wikidata":"https://www.wikidata.org/wiki/Q28455645","display_name":"Instruction prefetch","level":3,"score":0.730525016784668},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6713480949401855},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5972211360931396},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.5670281648635864},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.5596214532852173},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.47256866097450256},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.46770355105400085},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.364014208316803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31130725145339966},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2971840500831604},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.18439963459968567}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3460231.3474246","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3460231.3474246","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3460231.3474246","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3460231.3474246","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3460231.3474246","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3460231.3474246","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.5,"display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3201621211.pdf","grobid_xml":"https://content.openalex.org/works/W3201621211.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W2029463952","https://openalex.org/W2044683010","https://openalex.org/W2143285027","https://openalex.org/W2153111836","https://openalex.org/W2168676170","https://openalex.org/W2169119149","https://openalex.org/W2289543008","https://openalex.org/W2512971201","https://openalex.org/W2798625028","https://openalex.org/W2939477673","https://openalex.org/W2953384591","https://openalex.org/W2984020950","https://openalex.org/W2996471668","https://openalex.org/W3010969086","https://openalex.org/W3038103902","https://openalex.org/W4245990204","https://openalex.org/W4247641071"],"related_works":["https://openalex.org/W2140324148","https://openalex.org/W2121199344","https://openalex.org/W2285914869","https://openalex.org/W3117515082","https://openalex.org/W2113441357","https://openalex.org/W3022537591","https://openalex.org/W2167639078","https://openalex.org/W2379283503","https://openalex.org/W2141676084","https://openalex.org/W2462146500"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"recommendation":[2,104,198],"models":[3],"(DLRMs)":[4],"are":[5],"typically":[6],"composed":[7],"of":[8,11,49,56,68,93,118,121,180,205],"two":[9,225],"sets":[10],"parameters:":[12],"large":[13,197,249],"embedding":[14,51,122,127,141,167,173],"tables":[15,52,123,128],"to":[16,29,88,111,139,194,229,239],"handle":[17,30],"sparse":[18],"categorical":[19],"inputs,":[20],"and":[21,148],"neural":[22],"networks":[23],"such":[24,80],"as":[25,46],"multi-layer":[26],"perceptrons":[27],"(MLPs)":[28],"dense":[31],"non-categorical":[32],"inputs.":[33],"Current":[34],"DLRM":[35],"training":[36,106,137],"practices":[37],"keep":[38],"both":[39],"these":[40],"parameters":[41,59],"in":[42,60,129,151,251],"GPU":[43,61,116,152,161,203,252],"memory.":[44,131],"But":[45],"the":[47,50,90,119,160,165,172,178],"size":[48,120,175],"grow,":[53],"this":[54,97],"practice":[55],"storing":[57,125],"model":[58,94,105,199,206,236],"memory":[62,153],"requires":[63],"dozens":[64],"or":[65],"even":[66],"hundreds":[67],"GPUs.":[69],"This":[70],"is":[71,192],"an":[72],"unsustainable":[73],"trend":[74],"with":[75,189,212],"severe":[76],"environmental":[77],"consequences.":[78],"Furthermore,":[79],"a":[81,85,109,114,196,201,232,240],"design":[82],"forces":[83],"only":[84],"few":[86],"conglomerates":[87],"be":[89],"gate":[91],"keepers":[92],"training.":[95,222],"In":[96],"work,":[98],"we":[99],"propose":[100],"cDLRM":[101,170,190,217,233],"which":[102],"democratizes":[103],"by":[107,124,145],"allowing":[108],"user":[110],"train":[112,195],"on":[113,159,244],"single":[115,202],"regardless":[117,204],"all":[126],"CPU":[130,133],"A":[132],"based":[134],"pre-processor":[135],"analyzes":[136],"batches":[138,147],"prefetch":[140],"table":[142,168,174],"slices":[143],"accessed":[144],"those":[146],"caches":[149],"them":[150],"just-in-time.":[154],"An":[155],"associated":[156],"caching":[157,215],"protocol":[158],"enables":[162,218],"efficiently":[163],"updating":[164],"cached":[166],"parameters.":[169],"decouples":[171],"demands":[176],"from":[177,248],"number":[179],"GPUs":[181],"needed":[182],"for":[183],"compute.":[184],"We":[185,208,223],"first":[186],"demonstrate":[187,210],"that":[188,211,231],"it":[191],"possible":[193],"using":[200],"size.":[207],"then":[209],"its":[213],"unique":[214],"strategy,":[216],"pure":[219],"data":[220],"parallel":[221],"use":[224],"publicly":[226],"available":[227],"datasets":[228],"show":[230],"achieves":[234],"identical":[235],"accuracy":[237],"compared":[238],"baseline":[241],"trained":[242],"completely":[243],"GPUs,":[245],"while":[246],"benefiting":[247],"reduction":[250],"demand.":[253]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
