{"id":"https://openalex.org/W3161014634","doi":"https://doi.org/10.26599/bdma.2021.9020004","title":"AIPerf: Automated machine learning as an AI-HPC benchmark","display_name":"AIPerf: Automated machine learning as an AI-HPC benchmark","publication_year":2021,"publication_date":"2021-05-12","ids":{"openalex":"https://openalex.org/W3161014634","doi":"https://doi.org/10.26599/bdma.2021.9020004","mag":"3161014634"},"language":"en","primary_location":{"id":"doi:10.26599/bdma.2021.9020004","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2021.9020004","pdf_url":"https://ieeexplore.ieee.org/ielx7/8254253/9430128/09430136.pdf","source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ieeexplore.ieee.org/ielx7/8254253/9430128/09430136.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070028902","display_name":"Zhixiang Ren","orcid":"https://orcid.org/0000-0002-4104-3790"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhixiang Ren","raw_affiliation_strings":["Peng Cheng National Laboratory, Shenzhen 518000, China"],"affiliations":[{"raw_affiliation_string":"Peng Cheng National Laboratory, Shenzhen 518000, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102788364","display_name":"Yongheng Liu","orcid":"https://orcid.org/0000-0003-4314-0065"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongheng Liu","raw_affiliation_strings":["Peng Cheng National Laboratory, Shenzhen 518000, China"],"affiliations":[{"raw_affiliation_string":"Peng Cheng National Laboratory, Shenzhen 518000, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070740231","display_name":"Tianhui Shi","orcid":"https://orcid.org/0009-0008-2418-4007"},"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":"Tianhui Shi","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054697474","display_name":"Lei Xie","orcid":"https://orcid.org/0000-0002-7669-1886"},"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":"Lei Xie","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034322739","display_name":"Yue Zhou","orcid":"https://orcid.org/0009-0006-9839-2947"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Zhou","raw_affiliation_strings":["Peng Cheng National Laboratory, Shenzhen 518000, China"],"affiliations":[{"raw_affiliation_string":"Peng Cheng National Laboratory, Shenzhen 518000, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071200777","display_name":"Jidong Zhai","orcid":"https://orcid.org/0000-0002-7656-6428"},"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":"Jidong Zhai","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016596981","display_name":"Youhui Zhang","orcid":"https://orcid.org/0000-0003-2333-3580"},"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"]},{"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"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youhui Zhang","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China","Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100086, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100086, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001666028","display_name":"Yunquan Zhang","orcid":"https://orcid.org/0000-0002-2618-5088"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"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"]},{"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":"Yunquan Zhang","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China","Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100086, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100086, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103141832","display_name":"Wenguang Chen","orcid":"https://orcid.org/0000-0002-4281-1018"},"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":"Wenguang Chen","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5070028902"],"corresponding_institution_ids":["https://openalex.org/I4210136793"],"apc_list":null,"apc_paid":null,"fwci":1.9201,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.85877321,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"4","issue":"3","first_page":"208","last_page":"220"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11181","display_name":"Advanced Data Storage Technologies","score":0.9799000024795532,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.9783999919891357,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.8432921171188354},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8312186598777771},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.8154881000518799},{"id":"https://openalex.org/keywords/supercomputer","display_name":"Supercomputer","score":0.7748578786849976},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6708911061286926},{"id":"https://openalex.org/keywords/suite","display_name":"Suite","score":0.616278886795044},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5172412991523743},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.5133954286575317},{"id":"https://openalex.org/keywords/performance-metric","display_name":"Performance metric","score":0.49002039432525635},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4886787235736847},{"id":"https://openalex.org/keywords/spark","display_name":"SPARK (programming language)","score":0.4583333134651184},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.38020482659339905},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3682332932949066},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3538973331451416},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.35019001364707947},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.33847376704216003},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33340805768966675}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8432921171188354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8312186598777771},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.8154881000518799},{"id":"https://openalex.org/C83283714","wikidata":"https://www.wikidata.org/wiki/Q121117","display_name":"Supercomputer","level":2,"score":0.7748578786849976},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6708911061286926},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.616278886795044},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5172412991523743},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.5133954286575317},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.49002039432525635},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4886787235736847},{"id":"https://openalex.org/C2781215313","wikidata":"https://www.wikidata.org/wiki/Q3493345","display_name":"SPARK (programming language)","level":2,"score":0.4583333134651184},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.38020482659339905},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3682332932949066},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3538973331451416},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.35019001364707947},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.33847376704216003},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33340805768966675},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.26599/bdma.2021.9020004","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2021.9020004","pdf_url":"https://ieeexplore.ieee.org/ielx7/8254253/9430128/09430136.pdf","source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:62df745ba665431ca9caa42ffd7d5f21","is_oa":true,"landing_page_url":"https://doaj.org/article/62df745ba665431ca9caa42ffd7d5f21","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Big Data Mining and Analytics, Vol 4, Iss 3, Pp 208-220 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.26599/bdma.2021.9020004","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2021.9020004","pdf_url":"https://ieeexplore.ieee.org/ielx7/8254253/9430128/09430136.pdf","source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3161014634.pdf","grobid_xml":"https://content.openalex.org/works/W3161014634.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1980287119","https://openalex.org/W1994197834","https://openalex.org/W2009332171","https://openalex.org/W2039708501","https://openalex.org/W2097117768","https://openalex.org/W2097998348","https://openalex.org/W2101234009","https://openalex.org/W2106411961","https://openalex.org/W2146930501","https://openalex.org/W2194775991","https://openalex.org/W2271840356","https://openalex.org/W2515080096","https://openalex.org/W2553303224","https://openalex.org/W2587014634","https://openalex.org/W2752879223","https://openalex.org/W2790501674","https://openalex.org/W2885311373","https://openalex.org/W2895432151","https://openalex.org/W2899771611","https://openalex.org/W2910096450","https://openalex.org/W2914016760","https://openalex.org/W2941332886","https://openalex.org/W2949264490","https://openalex.org/W2951104886","https://openalex.org/W2951607363","https://openalex.org/W2951846401","https://openalex.org/W2962745291","https://openalex.org/W2963446712","https://openalex.org/W2963628712","https://openalex.org/W2964024268","https://openalex.org/W2966284335","https://openalex.org/W2969984826","https://openalex.org/W2971624117","https://openalex.org/W2975638172","https://openalex.org/W2976353488","https://openalex.org/W2979245724","https://openalex.org/W2998790058","https://openalex.org/W3005880794","https://openalex.org/W3038680131","https://openalex.org/W3043273434","https://openalex.org/W4236797923","https://openalex.org/W4297775537","https://openalex.org/W4309845474","https://openalex.org/W6600009415","https://openalex.org/W6600339963","https://openalex.org/W6600669965","https://openalex.org/W6601630192","https://openalex.org/W6601667473","https://openalex.org/W6604344240","https://openalex.org/W6607606998","https://openalex.org/W6636858258"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2341842940","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2059640416","https://openalex.org/W2329895846"],"abstract_inverted_index":{"The":[0],"plethora":[1],"of":[2,18,31],"complex":[3],"Artificial":[4],"Intelligence":[5],"(AI)":[6],"algorithms":[7,105],"and":[8,50,69,110,117,136,158,183,194,201],"available":[9],"High-Performance":[10],"Computing":[11],"(HPC)":[12],"power":[13,49],"stimulates":[14],"the":[15,25,39,46,104,115,145,155,184,210],"expeditious":[16],"development":[17],"AI":[19,47,59,91,146],"components":[20],"with":[21,122,163,175],"heterogeneous":[22],"designs.":[23],"Consequently,":[24],"need":[26],"for":[27,209],"cross-stack":[28],"performance":[29,52],"benchmarking":[30],"AI-HPC":[32],"systems":[33,121,152],"has":[34],"rapidly":[35],"emerged.":[36],"In":[37],"particular,":[38],"defacto":[40],"HPC":[41],"benchmark,":[42],"LINPACK,":[43],"cannot":[44],"reflect":[45],"computing":[48],"input/output":[51],"without":[53],"a":[54,65,107,140,191,205],"representative":[55],"workload.":[56],"Current":[57],"popular":[58],"benchmarks,":[60],"such":[61],"as":[62,139],"MLPerf,":[63],"have":[64],"fixed":[66],"problem":[67],"size":[68],"therefore":[70],"limited":[71],"scalability.":[72,189],"To":[73],"address":[74],"these":[75],"issues,":[76],"we":[77],"propose":[78],"an":[79,134],"end-to-end":[80],"benchmark":[81,207],"suite":[82,208],"utilizing":[83],"automated":[84],"machinelearning,":[85],"which":[86,131],"not":[87],"only":[88],"represents":[89],"real":[90],"scenarios,":[92],"but":[93],"also":[94],"is":[95],"auto-adaptively":[96],"scalable":[97],"to":[98,113,143,153,172],"various":[99,151],"scales":[100],"ofmachines.":[101],"We":[102,125,148],"implement":[103],"in":[106,133],"highly":[108],"parallel":[109],"flexible":[111,192],"way":[112],"ensure":[114,154],"efficiency":[116],"optimizationpotential":[118],"on":[119,150],"diverse":[120],"customizable":[123],"configurations.":[124],"utilize":[126],"Operations":[127],"Per":[128],"Second":[129],"(OPS),":[130],"ismeasured":[132],"analytical":[135],"systematic":[137],"approach,":[138],"major":[141],"metric":[142],"quantify":[144],"performance.":[147],"performevaluations":[149],"benchmark's":[156],"stability":[157],"scalability,":[159],"from":[160],"4":[161],"nodes":[162,174],"32":[164],"NVIDIA":[165],"Tesla":[166],"T4":[167],"(56.1":[168],"Tera-OPS":[169],"measured)":[170],"up":[171],"512":[173],"4096":[176],"Huawei":[177],"Ascend":[178],"910":[179],"(194.53":[180],"Peta-OPS":[181],"measured),":[182],"results":[185],"show":[186],"near-linear":[187],"weak":[188],"With":[190],"workload":[193],"single":[195],"metric,":[196],"AIPerf":[197],"can":[198],"easily":[199],"scaleon":[200],"rank":[202],"AI-HPC,":[203],"providing":[204],"powerful":[206],"coming":[211],"supercomputing":[212],"era.":[213]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}
