{"id":"https://openalex.org/W3089760668","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207419","title":"Leveraging the Manycore Architecture of the Loihi Spiking Processor to Perform Quasi-Complete Constraint Satisfaction","display_name":"Leveraging the Manycore Architecture of the Loihi Spiking Processor to Perform Quasi-Complete Constraint Satisfaction","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3089760668","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207419","mag":"3089760668"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9207419","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207419","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","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/A5055959085","display_name":"Chris Yakopcic","orcid":"https://orcid.org/0000-0001-6401-272X"},"institutions":[{"id":"https://openalex.org/I127591826","display_name":"University of Dayton","ror":"https://ror.org/021v3qy27","country_code":"US","type":"education","lineage":["https://openalex.org/I127591826"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chris Yakopcic","raw_affiliation_strings":["Dept. Of Electrical and Computer Engineering, University of Dayton, Dayton, OH, USA"],"affiliations":[{"raw_affiliation_string":"Dept. Of Electrical and Computer Engineering, University of Dayton, Dayton, OH, USA","institution_ids":["https://openalex.org/I127591826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011048070","display_name":"Nayim Rahman","orcid":"https://orcid.org/0000-0001-9008-5762"},"institutions":[{"id":"https://openalex.org/I127591826","display_name":"University of Dayton","ror":"https://ror.org/021v3qy27","country_code":"US","type":"education","lineage":["https://openalex.org/I127591826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nayim Rahman","raw_affiliation_strings":["Dept. Of Electrical and Computer Engineering, University of Dayton, Dayton, OH, USA"],"affiliations":[{"raw_affiliation_string":"Dept. Of Electrical and Computer Engineering, University of Dayton, Dayton, OH, USA","institution_ids":["https://openalex.org/I127591826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024817240","display_name":"Tanvir Atahary","orcid":"https://orcid.org/0000-0002-0268-5002"},"institutions":[{"id":"https://openalex.org/I127591826","display_name":"University of Dayton","ror":"https://ror.org/021v3qy27","country_code":"US","type":"education","lineage":["https://openalex.org/I127591826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tanvir Atahary","raw_affiliation_strings":["Dept. Of Electrical and Computer Engineering, University of Dayton, Dayton, OH, USA"],"affiliations":[{"raw_affiliation_string":"Dept. Of Electrical and Computer Engineering, University of Dayton, Dayton, OH, USA","institution_ids":["https://openalex.org/I127591826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104090957","display_name":"Tarek M. Taha","orcid":null},"institutions":[{"id":"https://openalex.org/I127591826","display_name":"University of Dayton","ror":"https://ror.org/021v3qy27","country_code":"US","type":"education","lineage":["https://openalex.org/I127591826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tarek M. Taha","raw_affiliation_strings":["Dept. Of Electrical and Computer Engineering, University of Dayton, Dayton, OH, USA"],"affiliations":[{"raw_affiliation_string":"Dept. Of Electrical and Computer Engineering, University of Dayton, Dayton, OH, USA","institution_ids":["https://openalex.org/I127591826"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111847909","display_name":"Scott Douglass","orcid":null},"institutions":[{"id":"https://openalex.org/I2799950915","display_name":"Wright-Patterson Air Force Base","ror":"https://ror.org/0097e1k27","country_code":"US","type":"other","lineage":["https://openalex.org/I1330347796","https://openalex.org/I2799950915","https://openalex.org/I4210089612","https://openalex.org/I4210102105"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Scott Douglass","raw_affiliation_strings":["Human Effectiveness Directorate, Air Force Research Laboratory, Wright Patterson Air Force Base, OH, USA"],"affiliations":[{"raw_affiliation_string":"Human Effectiveness Directorate, Air Force Research Laboratory, Wright Patterson Air Force Base, OH, USA","institution_ids":["https://openalex.org/I2799950915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5055959085"],"corresponding_institution_ids":["https://openalex.org/I127591826"],"apc_list":null,"apc_paid":null,"fwci":0.3112,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.57639558,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9955999851226807,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9919999837875366,"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/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.8132333159446716},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7767188549041748},{"id":"https://openalex.org/keywords/constraint-satisfaction","display_name":"Constraint satisfaction","score":0.7372205853462219},{"id":"https://openalex.org/keywords/constraint-satisfaction-problem","display_name":"Constraint satisfaction problem","score":0.7085275650024414},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.5745204091072083},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5373972654342651},{"id":"https://openalex.org/keywords/backtracking","display_name":"Backtracking","score":0.49931979179382324},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4841635823249817},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.47047072649002075},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4619290232658386},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4544818699359894},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.43358585238456726},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3236297369003296},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.29782241582870483},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.255204439163208},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1425361931324005},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08939564228057861}],"concepts":[{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.8132333159446716},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7767188549041748},{"id":"https://openalex.org/C44616089","wikidata":"https://www.wikidata.org/wiki/Q30158686","display_name":"Constraint satisfaction","level":3,"score":0.7372205853462219},{"id":"https://openalex.org/C199622910","wikidata":"https://www.wikidata.org/wiki/Q1128326","display_name":"Constraint satisfaction problem","level":3,"score":0.7085275650024414},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.5745204091072083},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5373972654342651},{"id":"https://openalex.org/C156884757","wikidata":"https://www.wikidata.org/wiki/Q798554","display_name":"Backtracking","level":2,"score":0.49931979179382324},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4841635823249817},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.47047072649002075},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4619290232658386},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4544818699359894},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.43358585238456726},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3236297369003296},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29782241582870483},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.255204439163208},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1425361931324005},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08939564228057861},{"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/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9207419","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207419","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.9100000262260437,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1518705996","https://openalex.org/W1667614912","https://openalex.org/W2048051309","https://openalex.org/W2057361103","https://openalex.org/W2060956313","https://openalex.org/W2083204880","https://openalex.org/W2142785340","https://openalex.org/W2143934828","https://openalex.org/W2165372647","https://openalex.org/W2321609157","https://openalex.org/W2775855651","https://openalex.org/W2783525259","https://openalex.org/W2792794651","https://openalex.org/W2801020852","https://openalex.org/W2887425801","https://openalex.org/W2904026282","https://openalex.org/W2908079451","https://openalex.org/W2963821348","https://openalex.org/W2964000821","https://openalex.org/W2969335882","https://openalex.org/W2977853463","https://openalex.org/W3003876377","https://openalex.org/W3015799364","https://openalex.org/W3036805013","https://openalex.org/W3100658279","https://openalex.org/W4229840182","https://openalex.org/W4233090747","https://openalex.org/W6637229586","https://openalex.org/W6684615325","https://openalex.org/W6747040291","https://openalex.org/W6755947534","https://openalex.org/W6761313881","https://openalex.org/W6785600802","https://openalex.org/W6814292443"],"related_works":["https://openalex.org/W2091348864","https://openalex.org/W2569549435","https://openalex.org/W2784687883","https://openalex.org/W2354343466","https://openalex.org/W3014398131","https://openalex.org/W3122634451","https://openalex.org/W2997121997","https://openalex.org/W2188549339","https://openalex.org/W1576780029","https://openalex.org/W2101480270"],"abstract_inverted_index":{"In":[0,97,219],"many":[1,98],"cases,":[2,99],"low":[3,140,208],"power":[4,209],"autonomous":[5],"systems":[6],"need":[7],"to":[8,65,108,121,128,156,182,237],"make":[9],"decisions":[10],"extremely":[11],"efficiently.":[12],"However,":[13],"as":[14,106,139,141],"a":[15,22,56,66,129,207,216],"problem":[16,58,87,234],"space":[17],"becomes":[18,25],"more":[19],"complex,":[20],"finding":[21,125],"solution":[23,104,124,131,217],"quickly":[24,46],"nearly":[26],"impossible":[27],"using":[28,49],"traditional":[29],"computing":[30],"methods.":[31],"Thus,":[32,171],"in":[33,149,196,241],"this":[34,77,150,197],"work":[35,195],"we":[36,79,221],"show":[37,80,222],"that":[38,61,223],"constraint":[39,100,204,232],"satisfaction":[40,54,101,205,233],"problems":[41,102],"(CSPs)":[42],"can":[43,62],"be":[44,63],"solved":[45],"and":[47,169,246],"efficiently":[48],"spiking":[50,93,151,179,225],"neural":[51,180],"networks.":[52],"Constraint":[53],"is":[55,119,153,228],"general":[57],"solving":[59,235],"technique":[60],"applied":[64],"large":[67],"number":[68],"of":[69,76,83,115,159,166,191,203,214,243],"different":[70],"applications.":[71],"To":[72,188],"demonstrate":[73],"the":[74,84,90,112,116,123,157,163,172,184,189,194,200,231],"validity":[75],"algorithm,":[78],"successful":[81],"execution":[82],"Boolean":[85],"satisfiability":[86],"(SAT)":[88],"on":[89,206],"Intel":[91],"Loihi":[92,117],"neuromorphic":[94,211,226],"research":[95],"processor.":[96],"have":[103],"sets":[105],"opposed":[107],"single":[109],"solutions.":[110],"Therefore,":[111],"manycore":[113],"architecture":[114],"chip":[118],"used":[120],"parallelize":[122],"process,":[126],"leading":[127],"quasi-complete":[130],"set":[132],"generated":[133],"at":[134],"extreme":[135,239],"efficiency":[136,186],"(dynamic":[137],"energy":[138],"8":[142],"micro":[143],"joules":[144],"per":[145],"solution).":[146],"Power":[147],"consumption":[148],"processor":[152,212],"due":[154],"primarily":[155],"propagation":[158],"spikes,":[160],"which":[161],"are":[162],"key":[164],"drivers":[165],"data":[167],"movement":[168],"processing.":[170],"proposed":[173],"SAT":[174],"algorithm":[175],"was":[176],"customized":[177],"for":[178],"networks":[181],"achieve":[183],"greatest":[185],"gains.":[187],"best":[190],"our":[192],"knowledge,":[193],"paper":[198],"exhibits":[199],"first":[201],"implementation":[202],"embedded":[210,224],"capable":[213,229],"generating":[215],"set.":[218],"general,":[220],"hardware":[227],"parallelizing":[230],"process":[236],"yield":[238],"gains":[240],"terms":[242],"time,":[244],"power,":[245],"energy.":[247]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}