{"id":"https://openalex.org/W4383749754","doi":"https://doi.org/10.1109/ccgrid57682.2023.00044","title":"ScaMP: Scalable Meta-Parallelism for Deep Learning Search","display_name":"ScaMP: Scalable Meta-Parallelism for Deep Learning Search","publication_year":2023,"publication_date":"2023-05-01","ids":{"openalex":"https://openalex.org/W4383749754","doi":"https://doi.org/10.1109/ccgrid57682.2023.00044"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccgrid57682.2023.00044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","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/A5015153122","display_name":"Quentin Anthony","orcid":"https://orcid.org/0000-0002-6823-9080"},"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":"Quentin Anthony","raw_affiliation_strings":["Department of Computer Science and Engineering, The Ohio State University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101847978","display_name":"Lang Xu","orcid":"https://orcid.org/0009-0000-6307-4566"},"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":"Lang Xu","raw_affiliation_strings":["Department of Computer Science and Engineering, The Ohio State University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078128277","display_name":"Aamir Shafi","orcid":"https://orcid.org/0000-0002-1924-2769"},"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":"Aamir Shafi","raw_affiliation_strings":["Department of Computer Science and Engineering, The Ohio State University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034293705","display_name":"Hari Subramoni","orcid":"https://orcid.org/0000-0002-1200-2754"},"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":"Hari Subramoni","raw_affiliation_strings":["Department of Computer Science and Engineering, The Ohio State University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024879682","display_name":"Dhabaleswar K. Panda","orcid":"https://orcid.org/0000-0002-0356-1781"},"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":"Dhabaleswar K. DK Panda","raw_affiliation_strings":["Department of Computer Science and Engineering, The Ohio State University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":70},"biblio":{"volume":"76","issue":null,"first_page":"391","last_page":"402"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Deep Learning in Computer Vision and Image Recognition","score":0.9999,"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":"Deep Learning in Computer Vision and Image Recognition","score":0.9999,"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/T10627","display_name":"Image Feature Retrieval and Recognition Techniques","score":0.9979,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9972,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep Learning","score":0.558232},{"id":"https://openalex.org/keywords/feature-matching","display_name":"Feature Matching","score":0.534446},{"id":"https://openalex.org/keywords/semantic-segmentation","display_name":"Semantic Segmentation","score":0.525053},{"id":"https://openalex.org/keywords/neural-network-architectures","display_name":"Neural Network Architectures","score":0.51273},{"id":"https://openalex.org/keywords/cross-modal-retrieval","display_name":"Cross-Modal Retrieval","score":0.507878}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.83165544},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7612133},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5138145},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47482714},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.44917625},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.44379485},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.42945835},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.40844843},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35919204},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.101692975},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccgrid57682.2023.00044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[{"funder":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation","award_id":"1818253,1854828,1931537,2007991,2018627,2112606"}],"datasets":[],"versions":[],"referenced_works_count":63,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1585237817","https://openalex.org/W1791560514","https://openalex.org/W1885185971","https://openalex.org/W1930824406","https://openalex.org/W2016482162","https://openalex.org/W2035677848","https://openalex.org/W2047920195","https://openalex.org/W2113207845","https://openalex.org/W2121927366","https://openalex.org/W2149669120","https://openalex.org/W2157494358","https://openalex.org/W2160635556","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2242218935","https://openalex.org/W2503458650","https://openalex.org/W2580688187","https://openalex.org/W2741137940","https://openalex.org/W2798926734","https://openalex.org/W2866634454","https://openalex.org/W2883265831","https://openalex.org/W2884711234","https://openalex.org/W2919115771","https://openalex.org/W2926655273","https://openalex.org/W2943530662","https://openalex.org/W2947737663","https://openalex.org/W2949676527","https://openalex.org/W2952046647","https://openalex.org/W2963351145","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2964081807","https://openalex.org/W2964101377","https://openalex.org/W2965658867","https://openalex.org/W2973727699","https://openalex.org/W3011655242","https://openalex.org/W3012220622","https://openalex.org/W3035022492","https://openalex.org/W3040573126","https://openalex.org/W3101659800","https://openalex.org/W3118781290","https://openalex.org/W3129831491","https://openalex.org/W3131068743","https://openalex.org/W3132977829","https://openalex.org/W3138516171","https://openalex.org/W3171125843","https://openalex.org/W3174394143","https://openalex.org/W3177196615","https://openalex.org/W3202742610","https://openalex.org/W3204801262","https://openalex.org/W3207918547","https://openalex.org/W4221167110","https://openalex.org/W4280611847","https://openalex.org/W4285297247","https://openalex.org/W4286909525","https://openalex.org/W4287765479","https://openalex.org/W4292779060","https://openalex.org/W4300223128","https://openalex.org/W4300427683","https://openalex.org/W4301239768","https://openalex.org/W4384705436","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W4401278057","https://openalex.org/W4247536566","https://openalex.org/W4241418540","https://openalex.org/W3119814709","https://openalex.org/W2725786787","https://openalex.org/W2404647514","https://openalex.org/W2018477250","https://openalex.org/W1875930651","https://openalex.org/W1667647204","https://openalex.org/W1508895727"],"abstract_inverted_index":{"Deep":[0,74],"Learning":[1,75],"(DL)":[2],"models":[3,92],"are":[4,157],"growing":[5],"exponentially":[6],"and":[7,29,43,55,83,105,115,135,142,153,175,192,208],"require":[8],"increasingly":[9],"powerful":[10,122],"High":[11],"Performance":[12],"Computing":[13],"(HPC)":[14],"systems":[15],"to":[16,39,228],"train":[17],"them.":[18],"Achieving":[19],"state-of-the-art":[20,179,241],"results":[21],"requires":[22],"carefully":[23],"tuning":[24],"the":[25,57,101,128,138,148,166,206,218,234],"DL":[26,59,64,103,189],"model":[27,190],"architecture":[28,134],"training":[30,110,173,177,239],"settings,":[31],"which":[32],"is":[33,98],"a":[34,50,78,121,178,187,194,215,240],"time-consuming":[35],"process":[36],"commonly":[37],"relegated":[38],"distributed":[40,79],"search":[41,46],"frameworks":[42,47],"trial-and-error.":[44],"However,":[45],"don't":[48],"provide":[49],"flexible":[51,94,161],"parallelism":[52,95],"scheme":[53],"within":[54],"among":[56],"chosen":[58],"framework":[60,88],"for":[61,73,147],"modern":[62,102],"out-of-core":[63,91],"models.":[65],"In":[66],"this":[67],"paper,":[68],"we":[69,213,231],"propose":[70],"Scalable":[71],"Meta-Parallelism":[72],"Search":[76,86],"(ScaMP):":[77],"Hyperparameter":[80],"Optimization":[81],"(HPO)":[82],"Neural":[84],"Architecture":[85],"(NAS)":[87],"that":[89],"supports":[90],"with":[93,155],"schemes.":[96],"SCaMP":[97,126,156,237],"integrated":[99],"into":[100],"ecosystem,":[104],"enables":[106],"both":[107],"efficient":[108],"parallel":[109],"of":[111,131,168,220,236],"concurrent":[112],"candidate":[113,133,188],"architectures":[114],"aggregate":[116],"device":[117],"memory":[118,129],"saturation":[119],"via":[120,160],"load":[123],"balancing":[124],"engine.":[125],"estimates":[127],"requirements":[130],"each":[132],"automatically":[136],"applies":[137],"appropriate":[139],"model-parallel":[140],"degree":[141],"maximum":[143],"batch":[144],"size":[145],"supported":[146],"given":[149],"candidate.":[150],"Further,":[151,212],"HPO":[152,199],"NAS":[154,221],"highly":[158],"customizable":[159],"configuration":[162],"options.":[163],"We":[164,183],"evaluate":[165],"benefits":[167],"our":[169],"designs":[170],"on":[171,201,205],"synthetic":[172],"benchmarks":[174],"in":[176,197,217,224],"vision":[180],"transformer":[181],"model.":[182,243],"select":[184],"transformers":[185],"as":[186],"type":[191],"demonstrate":[193,214],"29%":[195],"improvement":[196],"end-to-end":[198],"time":[200,222],"32":[202],"V100":[203],"GPUs":[204],"Lassen":[207],"ThetaGPU":[209],"HPC":[210],"systems.":[211],"reduction":[216],"proportion":[219],"spent":[223],"communication":[225],"from":[226],"28%":[227],"15%.":[229],"Finally,":[230],"thoroughly":[232],"verify":[233],"correctness":[235],"by":[238],"SwinIR":[242]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4383749754","counts_by_year":[],"updated_date":"2024-10-14T18:55:24.112704","created_date":"2023-07-11"}
