{"id":"https://openalex.org/W4414198889","doi":"https://doi.org/10.1109/dac63849.2025.11132454","title":"BiNeuroRAM: Energy-Efficient ReRAM-Based PIM for Accurate Bipolar Spiking Neural Network Acceleration","display_name":"BiNeuroRAM: Energy-Efficient ReRAM-Based PIM for Accurate Bipolar Spiking Neural Network Acceleration","publication_year":2025,"publication_date":"2025-06-22","ids":{"openalex":"https://openalex.org/W4414198889","doi":"https://doi.org/10.1109/dac63849.2025.11132454"},"language":"en","primary_location":{"id":"doi:10.1109/dac63849.2025.11132454","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dac63849.2025.11132454","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 62nd ACM/IEEE Design Automation Conference (DAC)","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/A5021873923","display_name":"Jun Yan Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jun Yan Lee","raw_affiliation_strings":["Shanghai Jiao Tong University,Intelligent Computing Research Group, SEIEE,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Intelligent Computing Research Group, SEIEE,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043209724","display_name":"Chen Nie","orcid":"https://orcid.org/0000-0002-8811-156X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Nie","raw_affiliation_strings":["Shanghai Jiao Tong University,Intelligent Computing Research Group, SEIEE,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Intelligent Computing Research Group, SEIEE,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005516309","display_name":"Kang Soo You","orcid":"https://orcid.org/0009-0009-5685-2521"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kang You","raw_affiliation_strings":["Shanghai Jiao Tong University,Intelligent Computing Research Group, SEIEE,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Intelligent Computing Research Group, SEIEE,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016892406","display_name":"Yueyang Jia","orcid":"https://orcid.org/0000-0003-3663-9765"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueyang Jia","raw_affiliation_strings":["University of Michigan - Shanghai Jiao Tong University Joint Institute,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"University of Michigan - Shanghai Jiao Tong University Joint Institute,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100614868","display_name":"Rui Yang","orcid":"https://orcid.org/0000-0003-4552-584X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Yang","raw_affiliation_strings":["Shanghai Jiao Tong University,Intelligent Computing Research Group, SEIEE,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Intelligent Computing Research Group, SEIEE,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036755436","display_name":"Zhezhi He","orcid":"https://orcid.org/0000-0002-6357-236X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhezhi He","raw_affiliation_strings":["Shanghai Jiao Tong University,Intelligent Computing Research Group, SEIEE,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Intelligent Computing Research Group, SEIEE,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5021873923"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23454877,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9962999820709229,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9922000169754028,"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":0.6215999722480774},{"id":"https://openalex.org/keywords/resistive-random-access-memory","display_name":"Resistive random-access memory","score":0.6122999787330627},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.5486000180244446},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.5418999791145325},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.521399974822998},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5149000287055969},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.4878000020980835},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4763000011444092}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.765999972820282},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.6215999722480774},{"id":"https://openalex.org/C182019814","wikidata":"https://www.wikidata.org/wiki/Q1143830","display_name":"Resistive random-access memory","level":3,"score":0.6122999787330627},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.5486000180244446},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5418999791145325},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.521399974822998},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5149000287055969},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.4878000020980835},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4763000011444092},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.45809999108314514},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.44909998774528503},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.44850000739097595},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.42260000109672546},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.40610000491142273},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.3831000030040741},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37070000171661377},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.36489999294281006},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.2531000077724457}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dac63849.2025.11132454","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dac63849.2025.11132454","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 62nd ACM/IEEE Design Automation Conference (DAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1604973310","https://openalex.org/W1906827922","https://openalex.org/W1916668514","https://openalex.org/W2010202670","https://openalex.org/W2071429830","https://openalex.org/W2108598243","https://openalex.org/W2159951683","https://openalex.org/W2194775991","https://openalex.org/W2775079417","https://openalex.org/W2783525259","https://openalex.org/W2990793844","https://openalex.org/W3006426821","https://openalex.org/W3026786299","https://openalex.org/W4236302577","https://openalex.org/W4292121737","https://openalex.org/W4385417471","https://openalex.org/W4386825396","https://openalex.org/W4387070976","https://openalex.org/W4387250054","https://openalex.org/W4390693311","https://openalex.org/W4391341605","https://openalex.org/W4394585928","https://openalex.org/W4413144679"],"related_works":[],"abstract_inverted_index":{"ReRAM":[0,74],"is":[1,42],"a":[2,25,66],"promising":[3],"non-volatile":[4],"memory":[5],"for":[6],"neuromor-phic":[7],"accelerators,":[8],"yet":[9],"it":[10],"faces":[11],"challenges":[12],"such":[13],"as":[14],"high":[15],"sensing":[16],"power":[17,76],"and":[18,104,109],"accuracy":[19,54],"degradation.":[20],"This":[21],"work":[22],"proposes":[23],"BiNeuroRAM,":[24],"novel":[26],"spiking":[27],"neural":[28],"network":[29],"(SNN)":[30],"accelerator":[31],"leveraging":[32],"ReRAM-based":[33],"processing-in-memory":[34],"(PIM),":[35],"with":[36,113],"three":[37],"key":[38],"contributions:":[39],"(1)":[40],"It":[41,64,83],"the":[43,60,91],"first":[44],"to":[45,116],"support":[46],"higher-accuracy":[47],"spike-tracing":[48],"bipolar-integrate-and-fire":[49],"(ST-BIF)":[50],"neurons,":[51],"achieving":[52],"80.9%":[53],"on":[55,111],"ImageNet,":[56],"8.4%":[57],"higher":[58],"than":[59],"previous":[61],"state-of-the-art;":[62],"(2)":[63],"introduces":[65],"low-power":[67],"voltage":[68],"sense":[69],"amplifier":[70],"(LPVSA)":[71],"that":[72,88,99],"reduces":[73],"read":[75],"by":[77,107],"14.7~58.2\u00d7,":[78],"enhancing":[79],"energy":[80,105],"efficiency;":[81],"(3)":[82],"employs":[84],"an":[85],"asynchronous":[86],"micro-architecture":[87],"fully":[89],"exploits":[90],"event-driven":[92],"nature":[93],"of":[94],"SNNs.":[95],"Experimental":[96],"results":[97],"show":[98],"BiNeuroRAM":[100],"improves":[101],"throughput":[102],"density":[103],"efficiency":[106],"2.08\u00d7":[108],"2.09\u00d7":[110],"ImageNet":[112],"ResNet-18,":[114],"compared":[115],"traditional":[117],"integrate-and-fire":[118],"(IF)":[119],"neuron-based":[120],"SNN":[121],"accelerators.":[122]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}