{"id":"https://openalex.org/W3008072732","doi":"https://doi.org/10.1145/3373087.3375361","title":"Low Precision Floating Point Arithmetic for High Performance FPGA-based CNN Acceleration","display_name":"Low Precision Floating Point Arithmetic for High Performance FPGA-based CNN Acceleration","publication_year":2020,"publication_date":"2020-02-23","ids":{"openalex":"https://openalex.org/W3008072732","doi":"https://doi.org/10.1145/3373087.3375361","mag":"3008072732"},"language":"en","primary_location":{"id":"doi:10.1145/3373087.3375361","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3373087.3375361","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","raw_type":"proceedings-article"},"type":"preprint","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/A5100707380","display_name":"Chen Wu","orcid":"https://orcid.org/0000-0002-2492-0640"},"institutions":[{"id":"https://openalex.org/I2799798094","display_name":"UCLA Health","ror":"https://ror.org/01d88se56","country_code":"US","type":"funder","lineage":["https://openalex.org/I2799798094"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chen Wu","raw_affiliation_strings":["UCLA, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"UCLA, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I2799798094"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100350102","display_name":"Mingyu Wang","orcid":"https://orcid.org/0000-0001-5722-9752"},"institutions":[{"id":"https://openalex.org/I2799798094","display_name":"UCLA Health","ror":"https://ror.org/01d88se56","country_code":"US","type":"funder","lineage":["https://openalex.org/I2799798094"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingyu Wang","raw_affiliation_strings":["UCLA, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"UCLA, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I2799798094"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066732321","display_name":"Xinyuan Chu","orcid":"https://orcid.org/0009-0002-0773-7606"},"institutions":[{"id":"https://openalex.org/I2799798094","display_name":"UCLA Health","ror":"https://ror.org/01d88se56","country_code":"US","type":"funder","lineage":["https://openalex.org/I2799798094"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinyuan Chu","raw_affiliation_strings":["UCLA, LOS ANGELES, CA, USA"],"affiliations":[{"raw_affiliation_string":"UCLA, LOS ANGELES, CA, USA","institution_ids":["https://openalex.org/I2799798094"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100366692","display_name":"Kun Wang","orcid":"https://orcid.org/0000-0002-9099-2781"},"institutions":[{"id":"https://openalex.org/I2799798094","display_name":"UCLA Health","ror":"https://ror.org/01d88se56","country_code":"US","type":"funder","lineage":["https://openalex.org/I2799798094"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kun Wang","raw_affiliation_strings":["UCLA, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"UCLA, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I2799798094"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007019142","display_name":"Lei He","orcid":"https://orcid.org/0000-0002-9875-9853"},"institutions":[{"id":"https://openalex.org/I2799798094","display_name":"UCLA Health","ror":"https://ror.org/01d88se56","country_code":"US","type":"funder","lineage":["https://openalex.org/I2799798094"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lei He","raw_affiliation_strings":["UCLA, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"UCLA, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I2799798094"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100707380"],"corresponding_institution_ids":["https://openalex.org/I2799798094"],"apc_list":null,"apc_paid":null,"fwci":1.76231458,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.86525648,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"318","last_page":"318"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9894000291824341,"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":0.9894000291824341,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9860000014305115,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7979994416236877},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7805538773536682},{"id":"https://openalex.org/keywords/floating-point","display_name":"Floating point","score":0.7465305924415588},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.7296113967895508},{"id":"https://openalex.org/keywords/fixed-point-arithmetic","display_name":"Fixed-point arithmetic","score":0.6015558242797852},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5685014128684998},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5475072860717773},{"id":"https://openalex.org/keywords/double-precision-floating-point-format","display_name":"Double-precision floating-point format","score":0.5473511219024658},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.5424282550811768},{"id":"https://openalex.org/keywords/single-precision-floating-point-format","display_name":"Single-precision floating-point format","score":0.532934844493866},{"id":"https://openalex.org/keywords/hardware-acceleration","display_name":"Hardware acceleration","score":0.4152357578277588},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39722052216529846},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.389053612947464},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.3827890455722809},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34630119800567627},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.34080755710601807},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10297092795372009}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7979994416236877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7805538773536682},{"id":"https://openalex.org/C84211073","wikidata":"https://www.wikidata.org/wiki/Q117879","display_name":"Floating point","level":2,"score":0.7465305924415588},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.7296113967895508},{"id":"https://openalex.org/C163973906","wikidata":"https://www.wikidata.org/wiki/Q649900","display_name":"Fixed-point arithmetic","level":3,"score":0.6015558242797852},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5685014128684998},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5475072860717773},{"id":"https://openalex.org/C35912277","wikidata":"https://www.wikidata.org/wiki/Q1243369","display_name":"Double-precision floating-point format","level":3,"score":0.5473511219024658},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.5424282550811768},{"id":"https://openalex.org/C133095886","wikidata":"https://www.wikidata.org/wiki/Q1307173","display_name":"Single-precision floating-point format","level":3,"score":0.532934844493866},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.4152357578277588},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39722052216529846},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.389053612947464},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.3827890455722809},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34630119800567627},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.34080755710601807},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10297092795372009},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3373087.3375361","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3373087.3375361","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2000092506","https://openalex.org/W2169016399","https://openalex.org/W2012407419","https://openalex.org/W2142464516","https://openalex.org/W2053382486","https://openalex.org/W2770657582","https://openalex.org/W154830955","https://openalex.org/W2097013438","https://openalex.org/W1978352992","https://openalex.org/W4210510163"],"abstract_inverted_index":{"Low":[0],"precision":[1],"data":[2],"representation":[3],"is":[4],"important":[5],"to":[6,28],"reduce":[7],"storage":[8],"size":[9],"and":[10,34],"memory":[11],"access":[12],"for":[13,31,44],"convolutional":[14],"neural":[15],"networks":[16],"(CNNs).":[17],"Yet,":[18],"existing":[19],"methods":[20],"have":[21],"two":[22],"major":[23],"limitations:":[24],"(1)":[25],"requiring":[26],"re-training":[27],"maintain":[29],"accuracy":[30],"deep":[32],"CNNs,":[33],"(2)":[35],"needing":[36],"16-bit":[37],"floating":[38],"point":[39,43],"or":[40],"8-bit":[41],"fixed":[42],"a":[45],"good":[46],"accuracy.":[47]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}