{"id":"https://openalex.org/W4413411957","doi":"https://doi.org/10.1145/3721145.3725750","title":"DALdex: A DPU-Accelerated Persistent Learned Index via Incremental Learning","display_name":"DALdex: A DPU-Accelerated Persistent Learned Index via Incremental Learning","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4413411957","doi":"https://doi.org/10.1145/3721145.3725750"},"language":"en","primary_location":{"id":"doi:10.1145/3721145.3725750","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3721145.3725750","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3721145.3725750","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 39th ACM International Conference on Supercomputing","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/10.1145/3721145.3725750","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Aoyang Tong","orcid":"https://orcid.org/0009-0000-4460-2327"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Aoyang Tong","raw_affiliation_strings":["Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088998781","display_name":"Yu Hua","orcid":"https://orcid.org/0000-0001-7730-3796"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Hua","raw_affiliation_strings":["Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062037144","display_name":"Menglei Chen","orcid":"https://orcid.org/0000-0001-5782-2361"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Menglei Chen","raw_affiliation_strings":["Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":2.326,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.89897518,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"535","last_page":"549"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9987999796867371,"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/T10057","display_name":"Face and Expression Recognition","score":0.9987999796867371,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9968000054359436,"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":"Advanced Image and Video Retrieval Techniques","score":0.9944000244140625,"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/computer-science","display_name":"Computer science","score":0.6081830263137817},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.5710640549659729},{"id":"https://openalex.org/keywords/incremental-learning","display_name":"Incremental learning","score":0.5615094900131226},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32247433066368103},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.11663404107093811}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6081830263137817},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.5710640549659729},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.5615094900131226},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32247433066368103},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.11663404107093811}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3721145.3725750","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3721145.3725750","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3721145.3725750","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 39th ACM International Conference on Supercomputing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3721145.3725750","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3721145.3725750","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3721145.3725750","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 39th ACM International Conference on Supercomputing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3582018851","display_name":null,"funder_award_id":"U22B2022","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4009475621","display_name":null,"funder_award_id":"62125202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5348138716","display_name":null,"funder_award_id":"6212520","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4413411957.pdf","grobid_xml":"https://content.openalex.org/works/W4413411957.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W1422898865","https://openalex.org/W1973062929","https://openalex.org/W2010216838","https://openalex.org/W2028802049","https://openalex.org/W2030062409","https://openalex.org/W2033811947","https://openalex.org/W2429518132","https://openalex.org/W2433709474","https://openalex.org/W2526202524","https://openalex.org/W2889201433","https://openalex.org/W2945486614","https://openalex.org/W2948233700","https://openalex.org/W2950683227","https://openalex.org/W2951941091","https://openalex.org/W2952777853","https://openalex.org/W2962771342","https://openalex.org/W2975438130","https://openalex.org/W2979531022","https://openalex.org/W2999149038","https://openalex.org/W3000271263","https://openalex.org/W3010663313","https://openalex.org/W3013808246","https://openalex.org/W3033065823","https://openalex.org/W3086582093","https://openalex.org/W3103567827","https://openalex.org/W3103616267","https://openalex.org/W3121516856","https://openalex.org/W3164254023","https://openalex.org/W3173619271","https://openalex.org/W3191055283","https://openalex.org/W3205377733","https://openalex.org/W3205529667","https://openalex.org/W3205928774","https://openalex.org/W3207820050","https://openalex.org/W4206548428","https://openalex.org/W4210798430","https://openalex.org/W4220669418","https://openalex.org/W4246281707","https://openalex.org/W4283325454","https://openalex.org/W4284974261","https://openalex.org/W4292169167","https://openalex.org/W4312210066","https://openalex.org/W4312642611","https://openalex.org/W4318541520","https://openalex.org/W4381327165","https://openalex.org/W4381327166","https://openalex.org/W4381327335","https://openalex.org/W4381621971","https://openalex.org/W4383749424","https://openalex.org/W4399283082","https://openalex.org/W4399304239","https://openalex.org/W4399304281","https://openalex.org/W4399304518","https://openalex.org/W4400680576"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"The":[0],"Data":[1],"Process":[2],"Unit":[3],"(DPU)":[4],"specializes":[5],"in":[6,30],"offloading":[7],"CPUintensive":[8],"tasks":[9,115],"and":[10,28,51,74,106,141,158,178],"provides":[11],"efficient":[12],"fault":[13],"tolerance":[14],"through":[15],"hardware-level":[16],"isolation.This":[17],"brings":[18],"unique":[19],"opportunities":[20],"to":[21,43,60,86,89,116,154],"develop":[22],"persistent":[23,66,100,172],"indexes":[24,68,173],"with":[25,103],"high":[26,104],"performance":[27,50,105],"availability":[29],"High":[31],"Performance":[32],"Computing":[33],"(HPC)":[34],"systems.The":[35],"recent":[36],"learned":[37,67,101],"index":[38,102,131],"exploits":[39],"machine":[40],"learning":[41,122],"models":[42],"efficiently":[44],"fit":[45],"data":[46],"distributions,":[47],"exhibiting":[48],"superior":[49],"low":[52],"storage":[53],"costs,":[54],"which":[55],"is":[56,134],"a":[57,97,137],"promising":[58],"alternative":[59],"traditional":[61],"tree-based":[62],"range":[63],"indexes.However,":[64],"state-of-the-art":[65],"suffer":[69],"from":[70],"costly":[71],"model":[72,109,139],"retrainings":[73],"inefficient":[75,85],"recovery":[76,160],"mechanisms":[77],"based":[78,118],"on":[79,119],"Non-Volatile":[80],"Memory":[81],"(NVM),":[82],"making":[83],"them":[84],"be":[87],"offloaded":[88],"DPUs.To":[90],"address":[91],"these":[92],"challenges,":[93],"we":[94],"propose":[95],"DALdex,":[96],"CPU-DPU":[98],"hybrid":[99],"availability.To":[107],"mitigate":[108],"retraining":[110,114],"overheads,":[111],"DALdex":[112,127,146,169],"offloads":[113],"DPU":[117,153],"the":[120,148,162],"incremental":[121],"scheme.To":[123],"minimize":[124],"NVM":[125,179],"amplifications,":[126],"designs":[128],"an":[129,142],"NVM-friendly":[130],"structure":[132],"that":[133,168],"decoupled":[135],"into":[136],"DRAM-accelerated":[138],"layer":[140],"NVM-aware":[143],"block":[144],"layer.Moreover,":[145],"utilizes":[147],"hardware":[149],"isolation":[150],"feature":[151],"of":[152],"achieve":[155],"seamless":[156],"failover":[157],"instant":[159],"via":[161],"PCIe":[163],"bus.Extensive":[164],"evaluation":[165],"results":[166],"demonstrate":[167],"outperforms":[170],"state-of-theart":[171],"by":[174],"1.07-6.34with":[175],"minimal":[176],"DRAM":[177],"overheads.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
