{"id":"https://openalex.org/W4386859281","doi":"https://doi.org/10.1109/islped58423.2023.10244298","title":"Bridging the Gap Between Spiking Neural Networks &amp; LSTMs for Latency &amp; Energy Efficiency","display_name":"Bridging the Gap Between Spiking Neural Networks &amp; LSTMs for Latency &amp; Energy Efficiency","publication_year":2023,"publication_date":"2023-08-07","ids":{"openalex":"https://openalex.org/W4386859281","doi":"https://doi.org/10.1109/islped58423.2023.10244298"},"language":"en","primary_location":{"id":"doi:10.1109/islped58423.2023.10244298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/islped58423.2023.10244298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED)","raw_type":"proceedings-article"},"type":"article","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/A5017435097","display_name":"Gourav Datta","orcid":"https://orcid.org/0000-0002-5380-2619"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Gourav Datta","raw_affiliation_strings":["University of Southern California,Ming Hsieh Department of Electrical and Computer Engineering,USA","Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California,Ming Hsieh Department of Electrical and Computer Engineering,USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083883530","display_name":"Haoqin Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haoqin Deng","raw_affiliation_strings":["University of Southern California,Ming Hsieh Department of Electrical and Computer Engineering,USA","Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California,Ming Hsieh Department of Electrical and Computer Engineering,USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027304745","display_name":"Robert S. Aviles","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert Aviles","raw_affiliation_strings":["University of Southern California,Ming Hsieh Department of Electrical and Computer Engineering,USA","Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California,Ming Hsieh Department of Electrical and Computer Engineering,USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100376643","display_name":"Zeyu Liu","orcid":"https://orcid.org/0000-0002-8213-7005"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zeyu Liu","raw_affiliation_strings":["University of Southern California,Ming Hsieh Department of Electrical and Computer Engineering,USA","Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California,Ming Hsieh Department of Electrical and Computer Engineering,USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084205024","display_name":"Peter A. Beerel","orcid":"https://orcid.org/0000-0002-8283-0168"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter A. Beerel","raw_affiliation_strings":["University of Southern California,Ming Hsieh Department of Electrical and Computer Engineering,USA","Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California,Ming Hsieh Department of Electrical and Computer Engineering,USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5017435097"],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":0.4016,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60503531,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9986000061035156,"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":0.9958999752998352,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.8762456178665161},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.841933012008667},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.8104228377342224},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6246764063835144},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5634225010871887},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5317413210868835},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.49977612495422363},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49062100052833557},{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.4884006381034851},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4586153030395508},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.45583653450012207},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.4316660761833191},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.2521294951438904}],"concepts":[{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.8762456178665161},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.841933012008667},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.8104228377342224},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6246764063835144},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5634225010871887},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5317413210868835},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.49977612495422363},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49062100052833557},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.4884006381034851},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4586153030395508},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.45583653450012207},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.4316660761833191},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.2521294951438904},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/islped58423.2023.10244298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/islped58423.2023.10244298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.9100000262260437,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G7728769296","display_name":null,"funder_award_id":"CCF-1763747","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W134960717","https://openalex.org/W2112796928","https://openalex.org/W2138913040","https://openalex.org/W2159951683","https://openalex.org/W2797583228","https://openalex.org/W2963743287","https://openalex.org/W2963993350","https://openalex.org/W2964338223","https://openalex.org/W2973166416","https://openalex.org/W2981101011","https://openalex.org/W2984844508","https://openalex.org/W3007283957","https://openalex.org/W3015205410","https://openalex.org/W3023721287","https://openalex.org/W3038819247","https://openalex.org/W3046186692","https://openalex.org/W3047826181","https://openalex.org/W3092055689","https://openalex.org/W3097285691","https://openalex.org/W3099821402","https://openalex.org/W3104409553","https://openalex.org/W3126711481","https://openalex.org/W3138295892","https://openalex.org/W3169215542","https://openalex.org/W3183764009","https://openalex.org/W3184526936","https://openalex.org/W3197271168","https://openalex.org/W3203196551","https://openalex.org/W4221155907","https://openalex.org/W4221157818","https://openalex.org/W4280539093","https://openalex.org/W4286909703","https://openalex.org/W4298355310","https://openalex.org/W4300980424","https://openalex.org/W4385245566","https://openalex.org/W6605479355","https://openalex.org/W6739901393","https://openalex.org/W6749922295","https://openalex.org/W6750665317","https://openalex.org/W6771742384","https://openalex.org/W6782262041","https://openalex.org/W6790089871","https://openalex.org/W6796421320","https://openalex.org/W6802746064","https://openalex.org/W6844652965"],"related_works":["https://openalex.org/W3137378424","https://openalex.org/W2809732489","https://openalex.org/W4287780255","https://openalex.org/W3023361272","https://openalex.org/W4391092513","https://openalex.org/W4393235919","https://openalex.org/W4281699635","https://openalex.org/W4321472116","https://openalex.org/W3202619090","https://openalex.org/W3089892344"],"abstract_inverted_index":{"Spiking":[0],"Neural":[1],"Networks":[2],"(SNNs)":[3],"have":[4,128],"emerged":[5],"as":[6],"an":[7,49,209],"attractive":[8],"spatio-temporal":[9],"computing":[10],"paradigm":[11],"for":[12,40,122,145,148],"complex":[13],"vision":[14],"tasks.":[15,42],"However,":[16],"most":[17],"existing":[18],"works":[19],"yield":[20],"models":[21],"that":[22,59,111],"require":[23,133],"many":[24],"time":[25,73,115,195],"steps":[26,196],"and":[27,87,132,177],"do":[28],"not":[29],"leverage":[30],"the":[31,83,113,149,198],"inherent":[32],"temporal":[33,171],"dynamics":[34],"of":[35,93,189],"spiking":[36,51],"neural":[37],"networks,":[38],"even":[39],"sequential":[41,167],"Motivated":[43],"by":[44,67],"this":[45],"observation,":[46],"we":[47,77,104],"propose":[48,78,105],"optimized":[50],"long":[52,123],"short-term":[53],"memory":[54],"networks":[55],"(LSTM)":[56],"training":[57],"framework":[58,165],"involves":[60],"a":[61,89,106],"novel":[62,79],"ANN-to-SNN":[63],"conversion":[64],"framework,":[65],"followed":[66],"SNN":[68,114],"fine-tuning":[69],"via":[70],"backpropagation":[71],"through":[72],"(BPTT).":[74],"In":[75],"particular,":[76],"activation":[80,130],"functions":[81],"in":[82,138,159],"source":[84],"LSTM":[85,183],"architecture":[86],"convert":[88],"judiciously":[90],"selected":[91],"subset":[92],"them":[94],"to":[95,140],"leaky-integrate-and-fire":[96],"(LIF)":[97],"activations":[98],"with":[99,192,201],"optimal":[100],"bias":[101],"shifts.":[102],"Moreover,":[103],"pipelined":[107],"parallel":[108],"processing":[109],"scheme":[110],"hides":[112],"steps,":[116],"significantly":[117],"improving":[118],"system":[119],"latency,":[120],"especially":[121],"sequences.":[124],"The":[125],"resulting":[126],"SNNs":[127],"high":[129],"sparsity":[131],"only":[134,193],"accumulate":[135],"operations":[136],"(AC),":[137],"contrast":[139],"expensive":[141],"multiply-and-accumulates":[142],"(MAC)":[143],"needed":[144],"ANNs,":[146],"except":[147],"input":[150],"layer":[151],"when":[152],"using":[153],"direct":[154],"encoding,":[155],"yielding":[156],"significant":[157],"improvements":[158],"energy":[160,207],"efficiency.":[161],"We":[162,185],"evaluate":[163],"our":[164],"on":[166,181,197],"learning":[168],"tasks":[169],"including":[170],"MNIST,":[172],"Google":[173],"Speech":[174],"Commands":[175],"(GSC),":[176],"UCI":[178],"Smartphone":[179],"datasets":[180],"different":[182],"architectures.":[184],"obtain":[186],"test":[187],"accuracy":[188],"94.75":[190],"%":[191],"2":[194],"GSC":[199],"dataset":[200],"<tex":[202],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[203],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\sim":[204],"4.1\\times$</tex>":[205],"lower":[206],"than":[208],"iso-architecture":[210],"standard":[211],"LSTM.":[212]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
