{"id":"https://openalex.org/W3092044102","doi":"https://doi.org/10.1145/3477145.3477157","title":"Connection Pruning for Deep Spiking Neural Networks with On-Chip Learning","display_name":"Connection Pruning for Deep Spiking Neural Networks with On-Chip Learning","publication_year":2021,"publication_date":"2021-07-27","ids":{"openalex":"https://openalex.org/W3092044102","doi":"https://doi.org/10.1145/3477145.3477157","mag":"3092044102"},"language":"en","primary_location":{"id":"doi:10.1145/3477145.3477157","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3477145.3477157","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3477145.3477157","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conference on Neuromorphic Systems 2021","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3477145.3477157","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035091959","display_name":"Thao Nguyen","orcid":"https://orcid.org/0000-0002-9465-5694"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Thao N. N. Nguyen","raw_affiliation_strings":["National University of Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070594442","display_name":"Bharadwaj Veeravalli","orcid":"https://orcid.org/0000-0001-9000-1813"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Bharadwaj Veeravalli","raw_affiliation_strings":["National University of Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085588788","display_name":"Xuanyao Fong","orcid":"https://orcid.org/0000-0001-5939-7389"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Xuanyao Fong","raw_affiliation_strings":["National University of Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":0.7865,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.6992625,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12236","display_name":"Photoreceptor and optogenetics research","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.8376603126525879},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7845768928527832},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.6675460934638977},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6285712718963623},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5757436156272888},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5555263757705688},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.5436500906944275},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4903106987476349},{"id":"https://openalex.org/keywords/chip","display_name":"Chip","score":0.43821436166763306},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4315991699695587},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4239829182624817},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3903399109840393},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3504287600517273},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07101649045944214}],"concepts":[{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.8376603126525879},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7845768928527832},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6675460934638977},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6285712718963623},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5757436156272888},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5555263757705688},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.5436500906944275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4903106987476349},{"id":"https://openalex.org/C165005293","wikidata":"https://www.wikidata.org/wiki/Q1074500","display_name":"Chip","level":2,"score":0.43821436166763306},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4315991699695587},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4239829182624817},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3903399109840393},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3504287600517273},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07101649045944214},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3477145.3477157","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3477145.3477157","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3477145.3477157","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conference on Neuromorphic Systems 2021","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2010.04351","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.04351","pdf_url":"https://arxiv.org/pdf/2010.04351","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"pmh:oai:scholarbank.nus.edu.sg:10635/245763","is_oa":false,"landing_page_url":"https://scholarbank.nus.edu.sg/handle/10635/245763","pdf_url":null,"source":{"id":"https://openalex.org/S7407052290","display_name":"National University of Singapore","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Elements","raw_type":"Conference Paper"}],"best_oa_location":{"id":"doi:10.1145/3477145.3477157","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3477145.3477157","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3477145.3477157","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conference on Neuromorphic Systems 2021","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8999999761581421,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G1482925484","display_name":null,"funder_award_id":"Tier 1","funder_id":"https://openalex.org/F4320320751","funder_display_name":"Ministry of Education - Singapore"},{"id":"https://openalex.org/G5155372924","display_name":null,"funder_award_id":"A18A6b0057","funder_id":"https://openalex.org/F4320320696","funder_display_name":"Agency for Science, Technology and Research"},{"id":"https://openalex.org/G6450335944","display_name":null,"funder_award_id":"R-263-000-E16-114, R-263-000-D07-114","funder_id":"https://openalex.org/F4320320751","funder_display_name":"Ministry of Education - Singapore"}],"funders":[{"id":"https://openalex.org/F4320320696","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09"},{"id":"https://openalex.org/F4320320698","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49"},{"id":"https://openalex.org/F4320320751","display_name":"Ministry of Education - Singapore","ror":"https://ror.org/01kcva023"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3092044102.pdf","grobid_xml":"https://content.openalex.org/works/W3092044102.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1486852018","https://openalex.org/W1645800954","https://openalex.org/W1686810756","https://openalex.org/W1981445810","https://openalex.org/W2037030438","https://openalex.org/W2071147887","https://openalex.org/W2114766824","https://openalex.org/W2125389748","https://openalex.org/W2155904486","https://openalex.org/W2188922879","https://openalex.org/W2612662066","https://openalex.org/W2618255684","https://openalex.org/W2779025322","https://openalex.org/W2793802172","https://openalex.org/W2794667948","https://openalex.org/W2801844931","https://openalex.org/W2805837749","https://openalex.org/W2896611294","https://openalex.org/W2903590539","https://openalex.org/W2940297489","https://openalex.org/W2946600702","https://openalex.org/W2962835968","https://openalex.org/W2963248262","https://openalex.org/W2963739929","https://openalex.org/W2963966976","https://openalex.org/W2978865499","https://openalex.org/W2986628237","https://openalex.org/W2995289984","https://openalex.org/W2995439340","https://openalex.org/W3002435930","https://openalex.org/W3015764616","https://openalex.org/W3023721287","https://openalex.org/W3104409553","https://openalex.org/W3121127024","https://openalex.org/W3208074141","https://openalex.org/W4229069445","https://openalex.org/W4285719527","https://openalex.org/W6687424872"],"related_works":["https://openalex.org/W2111241003","https://openalex.org/W4200391368","https://openalex.org/W2355315220","https://openalex.org/W2210979487","https://openalex.org/W3126544799","https://openalex.org/W2074043759","https://openalex.org/W2316202402","https://openalex.org/W2373535795","https://openalex.org/W2373300491","https://openalex.org/W2082487009"],"abstract_inverted_index":{"Long":[0],"training":[1],"time":[2,52],"hinders":[3],"the":[4,7,15,23,40,50,54,58,70,88,93,104,116,124,139],"potential":[5],"of":[6,57,119],"deep,":[8],"large-scale":[9],"Spiking":[10],"Neural":[11],"Network":[12],"(SNN)":[13],"with":[14,69],"on-chip":[16,41,89],"learning":[17,47,51,90],"capability":[18],"to":[19,48,65,137],"be":[20,37],"realized":[21],"on":[22,123],"embedded":[24],"systems":[25],"hardware.":[26],"Our":[27],"work":[28],"proposes":[29],"a":[30,66],"novel":[31],"connection":[32],"pruning":[33,140],"approach":[34,64,122],"that":[35],"can":[36],"applied":[38,62],"during":[39],"Spike":[42,74],"Timing":[43],"Dependent":[44],"Plasticity":[45],"(STDP)-based":[46],"optimize":[49],"and":[53,77,83,91,111],"network":[55,94],"connectivity":[56,95,105],"deep":[59,67],"SNN.":[60],"We":[61],"our":[63,120],"SNN":[68],"Time":[71],"To":[72],"First":[73],"(TTFS)":[75],"coding":[76],"has":[78],"successfully":[79],"achieved":[80],"2.1x":[81],"speed-up":[82,110],"64%":[84],"energy":[85,113],"savings":[86,114],"in":[87,108,115],"reduced":[92],"by":[96],"92.83%,":[97],"without":[98],"incurring":[99],"any":[100],"accuracy":[101],"loss.":[102],"Moreover,":[103],"reduction":[106],"results":[107],"2.83x":[109],"78.24%":[112],"inference.":[117],"Evaluation":[118],"proposed":[121],"Field":[125],"Programmable":[126],"Gate":[127],"Array":[128],"(FPGA)":[129],"platform":[130],"revealed":[131],"0.56%":[132],"power":[133],"overhead":[134],"was":[135],"needed":[136],"implement":[138],"algorithm.":[141]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2020-10-15T00:00:00"}
