{"id":"https://openalex.org/W2962718439","doi":"https://doi.org/10.1145/3337821.3337892","title":"DLBooster","display_name":"DLBooster","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2962718439","doi":"https://doi.org/10.1145/3337821.3337892","mag":"2962718439"},"language":"en","primary_location":{"id":"doi:10.1145/3337821.3337892","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3337821.3337892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International Conference on Parallel Processing","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/A5060417049","display_name":"Cheng Yang","orcid":"https://orcid.org/0000-0001-7821-0030"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN","GB"],"is_corresponding":false,"raw_author_name":"Yang Cheng","raw_affiliation_strings":["Tsinghua University Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University Microsoft Research","institution_ids":["https://openalex.org/I4210164937","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380761","display_name":"Dan Li","orcid":"https://orcid.org/0000-0002-7581-8865"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Li","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013018586","display_name":"Zhiyuan Guo","orcid":"https://orcid.org/0000-0001-9557-9171"},"institutions":[{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]},{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN","IN"],"is_corresponding":false,"raw_author_name":"Zhiyuan Guo","raw_affiliation_strings":["Microsoft Research Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Beihang University","institution_ids":["https://openalex.org/I4210124949","https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109404905","display_name":"Binyao Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["CN","IN"],"is_corresponding":false,"raw_author_name":"Binyao Jiang","raw_affiliation_strings":["Microsoft Research Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930","https://openalex.org/I4210124949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045558068","display_name":"Jiaxin Lin","orcid":"https://orcid.org/0000-0001-6534-9471"},"institutions":[{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]},{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN","IN"],"is_corresponding":false,"raw_author_name":"Jiaxin Lin","raw_affiliation_strings":["Microsoft Research Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Beihang University","institution_ids":["https://openalex.org/I4210124949","https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084447592","display_name":"Xi Fan","orcid":"https://orcid.org/0000-0002-3202-1047"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["CN","IN"],"is_corresponding":false,"raw_author_name":"Xi Fan","raw_affiliation_strings":["Microsoft Research Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930","https://openalex.org/I4210124949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078941654","display_name":"Jinkun Geng","orcid":"https://orcid.org/0000-0002-6574-8349"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinkun Geng","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062400907","display_name":"Xinyi Yu","orcid":"https://orcid.org/0000-0001-8716-7687"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["CN","IN"],"is_corresponding":false,"raw_author_name":"Xinyi Yu","raw_affiliation_strings":["Microsoft Research Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930","https://openalex.org/I4210124949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078969904","display_name":"Wei Bai","orcid":"https://orcid.org/0000-0002-8898-8070"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Wei Bai","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067303374","display_name":"Lei Qu","orcid":"https://orcid.org/0000-0002-2129-5253"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lei Qu","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008757709","display_name":"Ran Shu","orcid":"https://orcid.org/0000-0002-2021-4917"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ran Shu","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011847644","display_name":"Peng Cheng","orcid":"https://orcid.org/0000-0002-1994-893X"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Peng Cheng","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100735357","display_name":"Yongqiang Xiong","orcid":"https://orcid.org/0000-0003-4175-0097"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yongqiang Xiong","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055302018","display_name":"Jianping Wu","orcid":"https://orcid.org/0000-0002-6698-3607"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianping Wu","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.915,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.8307278,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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":1.0,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9991999864578247,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9976000189781189,"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":0.8493661880493164},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6521027088165283},{"id":"https://openalex.org/keywords/testbed","display_name":"Testbed","score":0.6346017122268677},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5881233215332031},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.4571840465068817},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4465583562850952},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.41304242610931396},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41270768642425537},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4005514979362488},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.3935709595680237},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.38671213388442993},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.354536771774292},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34846585988998413},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.2631065249443054},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.16444122791290283}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8493661880493164},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6521027088165283},{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.6346017122268677},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5881233215332031},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.4571840465068817},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4465583562850952},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.41304242610931396},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41270768642425537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4005514979362488},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3935709595680237},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.38671213388442993},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.354536771774292},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34846585988998413},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.2631065249443054},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.16444122791290283},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3337821.3337892","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3337821.3337892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International Conference on Parallel Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W1667072054","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1984222112","https://openalex.org/W1984541135","https://openalex.org/W1995945562","https://openalex.org/W2036003010","https://openalex.org/W2051424225","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2120480077","https://openalex.org/W2155893237","https://openalex.org/W2166706236","https://openalex.org/W2186615578","https://openalex.org/W2194775991","https://openalex.org/W2402144811","https://openalex.org/W2498764059","https://openalex.org/W2593116425","https://openalex.org/W2618530766","https://openalex.org/W2622263826","https://openalex.org/W2734612440","https://openalex.org/W2745534091","https://openalex.org/W2755682530","https://openalex.org/W2759465730","https://openalex.org/W2761434131","https://openalex.org/W2769856846","https://openalex.org/W2798534715","https://openalex.org/W2884711234","https://openalex.org/W2887718373","https://openalex.org/W2903475457","https://openalex.org/W2905104204","https://openalex.org/W2919115771","https://openalex.org/W2919632853","https://openalex.org/W2950592884","https://openalex.org/W2951341874","https://openalex.org/W2952250911","https://openalex.org/W2952503983","https://openalex.org/W4206174637","https://openalex.org/W4234552385"],"related_works":["https://openalex.org/W2883256816","https://openalex.org/W2171408034","https://openalex.org/W3003320923","https://openalex.org/W2106140982","https://openalex.org/W2152313554","https://openalex.org/W2064303750","https://openalex.org/W1509300825","https://openalex.org/W3092582874","https://openalex.org/W2054620577","https://openalex.org/W2977327189"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"deep":[3],"learning":[4,16],"(DL)":[5],"has":[6],"prospered":[7],"again":[8],"due":[9],"to":[10,94,96],"improvements":[11],"in":[12,66,125,143],"both":[13],"computing":[14],"and":[15],"theory.":[17],"Emerging":[18],"studies":[19,48],"mostly":[20],"focus":[21],"on":[22,49,78,101],"the":[23,40,98,115,139],"acceleration":[24],"of":[25,43],"refining":[26],"DL":[27,45,52,106,127],"models":[28],"but":[29,129],"ignore":[30],"data":[31,35,86,102],"preprocessing":[32,36,57,87,103],"issues.":[33],"However,":[34],"can":[37,119],"significantly":[38],"affect":[39],"overall":[41],"performance":[42],"end-to-end":[44],"workflows.":[46],"Our":[47,108],"several":[50,126],"image":[51,122,145],"workloads":[53,93],"show":[54,111],"that":[55,89],"existing":[56,116],"backends":[58],"are":[59],"quite":[60],"inefficient:":[61],"they":[62],"either":[63],"perform":[64],"poorly":[65],"throughput":[67,124],"(30%":[68],"degradation)":[69],"or":[70],"burn":[71],"too":[72],"many":[73],"(>10)":[74],"CPU":[75,133],"cores.":[76,134],"Based":[77],"these":[79],"observations,":[80],"we":[81],"propose":[82],"DLBooster,":[83],"a":[84],"high-performance":[85],"pipeline":[88],"selectively":[90],"offloads":[91],"key":[92],"FPGAs,":[95],"fit":[97],"stringent":[99],"demands":[100],"for":[104],"cutting-edge":[105],"applications.":[107],"testbed":[109],"experiments":[110],"that,":[112],"compared":[113],"with":[114],"baselines,":[117],"DLBooster":[118],"achieve":[120],"1.35\u00d7~2.4\u00d7":[121],"processing":[123],"workloads,":[128],"consumes":[130],"only":[131],"1/10":[132],"Besides,":[135],"it":[136],"also":[137],"reduces":[138],"latency":[140],"by":[141],"1/3":[142],"online":[144],"inference.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2019-07-30T00:00:00"}
