{"id":"https://openalex.org/W4318541575","doi":"https://doi.org/10.1145/3575693.3575728","title":"DPACS: Hardware Accelerated Dynamic Neural Network Pruning through Algorithm-Architecture Co-design","display_name":"DPACS: Hardware Accelerated Dynamic Neural Network Pruning through Algorithm-Architecture Co-design","publication_year":2023,"publication_date":"2023-01-27","ids":{"openalex":"https://openalex.org/W4318541575","doi":"https://doi.org/10.1145/3575693.3575728"},"language":"en","primary_location":{"id":"doi:10.1145/3575693.3575728","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3575693.3575728","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3575693.3575728","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3575693.3575728","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026079724","display_name":"Yizhao Gao","orcid":"https://orcid.org/0000-0001-5673-3746"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yizhao Gao","raw_affiliation_strings":["University of Hong Kong, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016180604","display_name":"Baoheng Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Baoheng Zhang","raw_affiliation_strings":["University of Hong Kong, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102498323","display_name":"Xiaojuan Qi","orcid":"https://orcid.org/0000-0002-4285-1626"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiaojuan Qi","raw_affiliation_strings":["University of Hong Kong, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020581824","display_name":"Hayden Kwok\u2010Hay So","orcid":"https://orcid.org/0000-0002-6514-0237"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Hayden Kwok-Hay So","raw_affiliation_strings":["University of Hong Kong, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":1.577,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.88860726,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"237","last_page":"251"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10320","display_name":"Neural Networks and Applications","score":0.9939000010490417,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9925000071525574,"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/pruning","display_name":"Pruning","score":0.85739666223526},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.8337307572364807},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8291749358177185},{"id":"https://openalex.org/keywords/dataflow","display_name":"Dataflow","score":0.7514303922653198},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.611257791519165},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.5976315140724182},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5510768890380859},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5277422070503235},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.496582567691803},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.49583253264427185},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49048492312431335},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4688015580177307},{"id":"https://openalex.org/keywords/dataflow-architecture","display_name":"Dataflow architecture","score":0.42118072509765625},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.19172698259353638},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19100001454353333}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.85739666223526},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.8337307572364807},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8291749358177185},{"id":"https://openalex.org/C96324660","wikidata":"https://www.wikidata.org/wiki/Q205446","display_name":"Dataflow","level":2,"score":0.7514303922653198},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.611257791519165},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.5976315140724182},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5510768890380859},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5277422070503235},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.496582567691803},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.49583253264427185},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49048492312431335},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4688015580177307},{"id":"https://openalex.org/C176727019","wikidata":"https://www.wikidata.org/wiki/Q1172415","display_name":"Dataflow architecture","level":3,"score":0.42118072509765625},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.19172698259353638},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19100001454353333},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3575693.3575728","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3575693.3575728","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3575693.3575728","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2","raw_type":"proceedings-article"},{"id":"pmh:oai:hub.hku.hk:10722/324825","is_oa":false,"landing_page_url":"https://hub.hku.hk/handle/10722/324825","pdf_url":null,"source":{"id":"https://openalex.org/S4377196271","display_name":"The HKU Scholars Hub (University of Hong Kong)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I889458895","host_organization_name":"University of Hong Kong","host_organization_lineage":["https://openalex.org/I889458895"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference_Paper"}],"best_oa_location":{"id":"doi:10.1145/3575693.3575728","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3575693.3575728","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3575693.3575728","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G1712123036","display_name":null,"funder_award_id":"R7003-21","funder_id":"https://openalex.org/F4320321592","funder_display_name":"Research Grants Council, University Grants Committee"},{"id":"https://openalex.org/G7829576559","display_name":null,"funder_award_id":"147/2020","funder_id":"https://openalex.org/F4320324392","funder_display_name":"Environment and Conservation Fund"}],"funders":[{"id":"https://openalex.org/F4320321592","display_name":"Research Grants Council, University Grants Committee","ror":"https://ror.org/00djwmt25"},{"id":"https://openalex.org/F4320324392","display_name":"Environment and Conservation Fund","ror":"https://ror.org/05tp8q545"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4318541575.pdf","grobid_xml":"https://content.openalex.org/works/W4318541575.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W566555209","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2549139847","https://openalex.org/W2562731582","https://openalex.org/W2565125333","https://openalex.org/W2604998962","https://openalex.org/W2623629680","https://openalex.org/W2625457103","https://openalex.org/W2736953746","https://openalex.org/W2752782242","https://openalex.org/W2884585870","https://openalex.org/W2891946740","https://openalex.org/W2904902077","https://openalex.org/W2924515500","https://openalex.org/W2945146780","https://openalex.org/W2948634622","https://openalex.org/W2950656546","https://openalex.org/W2962851801","https://openalex.org/W2962856739","https://openalex.org/W2962944050","https://openalex.org/W2963163009","https://openalex.org/W2963382930","https://openalex.org/W2963698820","https://openalex.org/W2963918968","https://openalex.org/W2979439447","https://openalex.org/W2979838629","https://openalex.org/W2980186997","https://openalex.org/W3010833785","https://openalex.org/W3035678286","https://openalex.org/W3040646053","https://openalex.org/W3109632933","https://openalex.org/W3132460984","https://openalex.org/W3132616766","https://openalex.org/W3168376295","https://openalex.org/W3184606595","https://openalex.org/W3216787071","https://openalex.org/W4213110004","https://openalex.org/W4214700987","https://openalex.org/W4240168186","https://openalex.org/W4251575795","https://openalex.org/W6926674847"],"related_works":["https://openalex.org/W2564598376","https://openalex.org/W1484403103","https://openalex.org/W2584408851","https://openalex.org/W2115158825","https://openalex.org/W2101960124","https://openalex.org/W4377693460","https://openalex.org/W2891987081","https://openalex.org/W2033683327","https://openalex.org/W2783505431","https://openalex.org/W2187181201"],"abstract_inverted_index":{"By":[0],"eliminating":[1],"compute":[2,52,94],"operations":[3,53,66,95],"intelligently":[4],"based":[5],"on":[6,28],"the":[7,73,78,83,91,101],"run":[8,71],"time":[9],"input,":[10],"dynamic":[11,80],"pruning":[12,37],"(DP)":[13],"promises":[14],"to":[15,46,67,75,100],"improve":[16],"deep":[17],"neural":[18],"network":[19],"inference":[20],"speed":[21],"substantially":[22],"without":[23],"incurring":[24],"a":[25,44],"major":[26],"impact":[27],"their":[29],"accuracy.":[30],"Although":[31],"many":[32],"DP":[33,106],"algorithms":[34],"with":[35],"good":[36],"performance":[38],"have":[39,97],"been":[40],"proposed,":[41],"it":[42],"remains":[43],"challenge":[45,102],"translate":[47],"these":[48],"theoretical":[49],"reductions":[50],"in":[51,58],"into":[54],"satisfactory":[55],"end-to-end":[56],"speedups":[57],"practical":[59,105],"real-world":[60],"implementations.":[61],"The":[62],"overhead":[63],"of":[64,93,103],"identifying":[65],"be":[68],"pruned":[69],"during":[70],"time,":[72],"need":[74],"efficiently":[76],"process":[77],"resulting":[79],"dataflow,":[81],"and":[82],"non-trivial":[84],"memory":[85],"I/O":[86],"bottleneck":[87],"that":[88],"emerges":[89],"as":[90],"number":[92],"reduces,":[96],"all":[98],"contributed":[99],"implementing":[104],"systems.":[107]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}