{"id":"https://openalex.org/W4308659928","doi":"https://doi.org/10.1109/vlsi-soc54400.2022.9939647","title":"Toward Large Scale All-Optical Spiking Neural Networks","display_name":"Toward Large Scale All-Optical Spiking Neural Networks","publication_year":2022,"publication_date":"2022-10-03","ids":{"openalex":"https://openalex.org/W4308659928","doi":"https://doi.org/10.1109/vlsi-soc54400.2022.9939647"},"language":"en","primary_location":{"id":"doi:10.1109/vlsi-soc54400.2022.9939647","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vlsi-soc54400.2022.9939647","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IFIP/IEEE 30th International Conference on Very Large Scale Integration (VLSI-SoC)","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/A5056124225","display_name":"Milad Eslaminia","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Milad Eslaminia","raw_affiliation_strings":["Concordia University,Department of Electrical and Computer Engineering,Montréal,Canada"],"affiliations":[{"raw_affiliation_string":"Concordia University,Department of Electrical and Computer Engineering,Montréal,Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071008313","display_name":"S\u00e9bastien Le Beux","orcid":"https://orcid.org/0000-0003-1778-0253"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sebastien Le Beux","raw_affiliation_strings":["Concordia University,Department of Electrical and Computer Engineering,Montréal,Canada"],"affiliations":[{"raw_affiliation_string":"Concordia University,Department of Electrical and Computer Engineering,Montréal,Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5056124225"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11433702,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":1.0,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9993000030517578,"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/T10232","display_name":"Optical Network Technologies","score":0.9923999905586243,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7705000638961792},{"id":"https://openalex.org/keywords/synaptic-weight","display_name":"Synaptic weight","score":0.695275604724884},{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.6749348640441895},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.6549115180969238},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6291266679763794},{"id":"https://openalex.org/keywords/multiplexing","display_name":"Multiplexing","score":0.5227468013763428},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.48526570200920105},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.41634470224380493},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4156542420387268},{"id":"https://openalex.org/keywords/wavelength-division-multiplexing","display_name":"Wavelength-division multiplexing","score":0.410767138004303},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.3749842643737793},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.33643218874931335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2653830647468567},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1340385377407074},{"id":"https://openalex.org/keywords/wavelength","display_name":"Wavelength","score":0.130784809589386},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.08980163931846619},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08734017610549927},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.07760888338088989}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7705000638961792},{"id":"https://openalex.org/C66949984","wikidata":"https://www.wikidata.org/wiki/Q7662043","display_name":"Synaptic weight","level":3,"score":0.695275604724884},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.6749348640441895},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.6549115180969238},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6291266679763794},{"id":"https://openalex.org/C19275194","wikidata":"https://www.wikidata.org/wiki/Q222903","display_name":"Multiplexing","level":2,"score":0.5227468013763428},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.48526570200920105},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.41634470224380493},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4156542420387268},{"id":"https://openalex.org/C160724564","wikidata":"https://www.wikidata.org/wiki/Q1620670","display_name":"Wavelength-division multiplexing","level":3,"score":0.410767138004303},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3749842643737793},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.33643218874931335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2653830647468567},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1340385377407074},{"id":"https://openalex.org/C6260449","wikidata":"https://www.wikidata.org/wiki/Q41364","display_name":"Wavelength","level":2,"score":0.130784809589386},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.08980163931846619},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08734017610549927},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.07760888338088989},{"id":"https://openalex.org/C49040817","wikidata":"https://www.wikidata.org/wiki/Q193091","display_name":"Optoelectronics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vlsi-soc54400.2022.9939647","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vlsi-soc54400.2022.9939647","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IFIP/IEEE 30th International Conference on Very Large Scale Integration (VLSI-SoC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2006370340","https://openalex.org/W2007339694","https://openalex.org/W2512481274","https://openalex.org/W2593589516","https://openalex.org/W2752849906","https://openalex.org/W2758404936","https://openalex.org/W2898323475","https://openalex.org/W2898583937","https://openalex.org/W2910306093","https://openalex.org/W2911001665","https://openalex.org/W2944119451","https://openalex.org/W2976594647","https://openalex.org/W3087727356","https://openalex.org/W3088599523","https://openalex.org/W3096230432","https://openalex.org/W3097978562","https://openalex.org/W3128451613"],"related_works":["https://openalex.org/W3089892344","https://openalex.org/W2960220682","https://openalex.org/W4386227293","https://openalex.org/W4372267706","https://openalex.org/W2885510266","https://openalex.org/W4288055417","https://openalex.org/W4205804651","https://openalex.org/W4287758233","https://openalex.org/W3136467750","https://openalex.org/W4313442939"],"abstract_inverted_index":{"Silicon":[0],"Photonics":[1],"is":[2],"a":[3,50,62,71,89,153],"promising":[4],"technology":[5],"to":[6,27,91,106,122,138,151],"develop":[7],"neuromorphic":[8,45],"hardware":[9,47,72,108],"accelerators.":[10],"Most":[11],"optical":[12],"neural":[13,67,100,128],"networks":[14,68,129],"rely":[15],"on":[16,44,70,96,117,132],"wavelength":[17],"division":[18],"multiplexing":[19],"(WDM),":[20],"which":[21,79],"calls":[22],"for":[23,29],"power":[24,142],"hungry":[25],"calibration":[26],"compensate":[28],"non-uniformity":[30],"fabrication":[31],"process":[32],"and":[33,120,141],"thermal":[34],"variations":[35],"of":[36,53,66,76,148],"microring":[37],"resonators":[38],"(MRR).":[39],"This":[40],"imposes":[41],"practical":[42],"limits":[43],"photonic":[46],"since":[48],"only":[49],"small":[51],"number":[52],"synaptic":[54,77,124],"connections":[55],"per":[56],"neuron":[57],"can":[58],"be":[59],"implemented.":[60],"As":[61],"result,":[63],"the":[64,82,104,146],"mapping":[65],"(NN)":[69],"platform":[73],"require":[74],"pruning":[75],"connections,":[78],"drastically":[80],"affects":[81],"accuracy.":[83],"In":[84],"this":[85],"work,":[86],"we":[87,135],"propose":[88],"method":[90,115],"efficiently":[92],"map":[93],"pre-trained":[94],"NN":[95,155],"an":[97,133],"all-optical":[98],"spiking":[99],"network":[101],"(SNN),":[102],"with":[103,164],"aim":[105],"optimize":[107],"utilization":[109],"while":[110,156],"minimizing":[111],"accuracy":[112,140],"loss.":[113],"The":[114,126],"relies":[116],"weight":[118,149],"partitioning":[119,150],"unrolling":[121],"reduce":[123],"connections.":[125],"resulting":[127],"are":[130],"mapped":[131],"architecture":[134],"propose,":[136],"allowing":[137],"estimate":[139],"consumption.":[143],"Results":[144],"show":[145],"capability":[147],"implement":[152],"realistic":[154],"attaining":[157],"58%":[158],"reduction":[159],"in":[160],"energy":[161],"consumption":[162],"compared":[163],"unrolling.":[165]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}