{"id":"https://openalex.org/W2899219915","doi":"https://doi.org/10.1109/icccnt.2018.8494067","title":"Implementing a Neural Processor for Accelerating Deep Learning","display_name":"Implementing a Neural Processor for Accelerating Deep Learning","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2899219915","doi":"https://doi.org/10.1109/icccnt.2018.8494067","mag":"2899219915"},"language":"en","primary_location":{"id":"doi:10.1109/icccnt.2018.8494067","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt.2018.8494067","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT)","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/A5028591625","display_name":"Sreejith R Warrier","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sreejith R Warrier","raw_affiliation_strings":["Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054473733","display_name":"Senthil Murugan","orcid":"https://orcid.org/0000-0001-6428-1110"},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Senthil Murugan","raw_affiliation_strings":["Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, India","institution_ids":["https://openalex.org/I81556334"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I81556334"],"apc_list":null,"apc_paid":null,"fwci":0.338,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.69675385,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"26","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9991000294685364,"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/T10320","display_name":"Neural Networks and Applications","score":0.9991000294685364,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9850999712944031,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.984000027179718,"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":0.8307176828384399},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7604126930236816},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7288497090339661},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6527363657951355},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6097747087478638},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.5538623332977295},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.532914400100708},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5280095934867859},{"id":"https://openalex.org/keywords/hardware-acceleration","display_name":"Hardware acceleration","score":0.4665745496749878},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4516718089580536},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4432108998298645},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.4289216995239258},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37919026613235474},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.2343847155570984},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.18239280581474304},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.1295304000377655},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08233964443206787}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8307176828384399},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7604126930236816},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7288497090339661},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6527363657951355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6097747087478638},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.5538623332977295},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.532914400100708},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5280095934867859},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.4665745496749878},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4516718089580536},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4432108998298645},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.4289216995239258},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37919026613235474},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.2343847155570984},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.18239280581474304},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.1295304000377655},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08233964443206787},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccnt.2018.8494067","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt.2018.8494067","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W143296170","https://openalex.org/W1497408952","https://openalex.org/W1591178201","https://openalex.org/W1972458829","https://openalex.org/W1984020445","https://openalex.org/W2059300781","https://openalex.org/W2063071670","https://openalex.org/W2088079057","https://openalex.org/W2111777469","https://openalex.org/W2112796928","https://openalex.org/W2163605009","https://openalex.org/W2168665069","https://openalex.org/W2343910949","https://openalex.org/W2553282078","https://openalex.org/W2574916219","https://openalex.org/W2583031650","https://openalex.org/W6605830617","https://openalex.org/W6646626328"],"related_works":["https://openalex.org/W2565094479","https://openalex.org/W2390829436","https://openalex.org/W1989791859","https://openalex.org/W602859758","https://openalex.org/W2006439817","https://openalex.org/W1971289376","https://openalex.org/W2146872326","https://openalex.org/W3042419602","https://openalex.org/W2966649771","https://openalex.org/W3158825072"],"abstract_inverted_index":{"The":[0],"project":[1],"involves":[2],"the":[3,24,49,65],"design":[4],"and":[5,47,63,83],"development":[6],"of":[7,37,45,67,69,81,89],"a":[8,35,43,53,73,79,106,110],"neural":[9,32,57,91],"processor":[10],"architecture":[11],"for":[12,87,99,108],"accelerating":[13],"deep":[14,27],"learning.":[15],"Several":[16],"companies":[17],"are":[18,85,96],"investing":[19],"in":[20,26],"hardware":[21,112],"acceleration":[22],"as":[23],"interest":[25],"learning":[28],"is":[29,34,72,105],"growing.":[30],"A":[31],"network":[33],"combination":[36,80],"neurons":[38],"that":[39],"apply":[40],"weights":[41],"to":[42],"set":[44],"inputs":[46],"evaluate":[48],"output":[50],"based":[51],"on":[52],"nonlinear":[54],"function.":[55],"Deep":[56],"nets":[58],"have":[59],"several":[60],"such":[61,100],"nodes":[62,71],"evaluating":[64],"state":[66],"each":[68],"these":[70,90,94],"very":[74],"compute":[75],"intensive":[76],"task.":[77],"Currently":[78],"CPUs":[82],"GPUs":[84],"used":[86],"training/inference":[88],"nets,":[92],"but":[93],"processors":[95],"not":[97],"designated":[98],"heavy":[101],"workloads.":[102],"Hence":[103],"there":[104],"need":[107],"designing":[109],"specialized":[111],"this":[113],"application.":[114]},"counts_by_year":[{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
