{"id":"https://openalex.org/W4404133984","doi":"https://doi.org/10.1145/3649329.3657377","title":"EPIM: Efficient Processing-In-Memory Accelerators based on Epitome","display_name":"EPIM: Efficient Processing-In-Memory Accelerators based on Epitome","publication_year":2024,"publication_date":"2024-06-23","ids":{"openalex":"https://openalex.org/W4404133984","doi":"https://doi.org/10.1145/3649329.3657377"},"language":"en","primary_location":{"id":"doi:10.1145/3649329.3657377","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3649329.3657377","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 61st ACM/IEEE Design Automation Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3649329.3657377","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115605018","display_name":"Chenyu Wang","orcid":"https://orcid.org/0009-0001-8374-4659"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chenyu Wang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100631017","display_name":"Zhen Dong","orcid":"https://orcid.org/0000-0002-5951-6170"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhen Dong","raw_affiliation_strings":["University of California, Berkeley, Berkeley, CA, United States"],"affiliations":[{"raw_affiliation_string":"University of California, Berkeley, Berkeley, CA, United States","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072984967","display_name":"Daquan Zhou","orcid":"https://orcid.org/0000-0002-4771-1796"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daquan Zhou","raw_affiliation_strings":["Bytedance, Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Bytedance, Singapore, Singapore, Singapore","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103138440","display_name":"Zhenhua Zhu","orcid":"https://orcid.org/0009-0007-9259-7180"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhua Zhu","raw_affiliation_strings":["Tsinghua University, Beijing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052899986","display_name":"Yu Wang","orcid":"https://orcid.org/0000-0002-2931-8958"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Wang","raw_affiliation_strings":["Tsinghua University, Beijing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100668696","display_name":"Jiashi Feng","orcid":"https://orcid.org/0000-0001-6843-0064"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiashi Feng","raw_affiliation_strings":["ByteDance, Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"ByteDance, Singapore, Singapore, Singapore","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047285420","display_name":"Kurt Keutzer","orcid":"https://orcid.org/0000-0003-3868-8501"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kurt Keutzer","raw_affiliation_strings":["University of California, Berkeley, Berkeley, CA, United States"],"affiliations":[{"raw_affiliation_string":"University of California, Berkeley, Berkeley, CA, United States","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5115605018"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17841369,"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":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9984999895095825,"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":0.9984999895095825,"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/T11407","display_name":"Innovative Microfluidic and Catalytic Techniques Innovation","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9879999756813049,"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/epitome","display_name":"Epitome","score":0.9531748294830322},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7075302600860596},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.11637362837791443}],"concepts":[{"id":"https://openalex.org/C2775858994","wikidata":"https://www.wikidata.org/wiki/Q5383732","display_name":"Epitome","level":2,"score":0.9531748294830322},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7075302600860596},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.11637362837791443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3649329.3657377","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3649329.3657377","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 61st ACM/IEEE Design Automation Conference","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3649329.3657377","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3649329.3657377","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 61st ACM/IEEE Design Automation Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.550000011920929,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2508602506","https://openalex.org/W2518281301","https://openalex.org/W2946659370","https://openalex.org/W2982041622","https://openalex.org/W3013241373","https://openalex.org/W3022053993","https://openalex.org/W3083443371","https://openalex.org/W3091922395"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W3151712336","https://openalex.org/W2051533144","https://openalex.org/W3006807070","https://openalex.org/W4231592335","https://openalex.org/W564987741","https://openalex.org/W1995642259","https://openalex.org/W1998990477"],"abstract_inverted_index":{"The":[0],"utilization":[1],"of":[2,32,38,58,138,148],"large-scale":[3],"neural":[4,45,59,62,66,90],"networks":[5],"on":[6,114,178,191],"Processing-In-Memory":[7],"(PIM)":[8],"accelerators":[9,102,116,151],"encounters":[10],"challenges":[11],"due":[12],"to":[13,28,43,68,95,124,133,152,162],"constrained":[14],"on-chip":[15],"memory":[16],"capacity.":[17],"To":[18],"tackle":[19],"this":[20,82],"issue,":[21],"current":[22,149],"works":[23],"explore":[24],"model":[25],"compression":[26],"algorithms":[27,40],"reduce":[29,135,163],"the":[30,55,86,105,136,141,146,187],"size":[31,137],"Convolutional":[33],"Neural":[34],"Networks":[35],"(CNNs).":[36],"Most":[37],"these":[39],"either":[41],"aim":[42],"represent":[44],"operators":[46,60,67,99],"with":[47,70],"reduced-size":[48],"parameters":[49],"(e.g.,":[50,61],"quantization)":[51],"or":[52],"search":[53],"for":[54,100],"best":[56],"combinations":[57],"architecture":[63],"search).":[64],"Designing":[65],"align":[69],"PIM":[71,101,115,150],"accelerators'":[72],"specifications":[73],"is":[74],"an":[75],"area":[76],"that":[77,169],"warrants":[78],"further":[79,134],"study.":[80],"In":[81],"paper,":[83],"we":[84,108,144],"introduce":[85,118],"Epitome,":[87],"a":[88,119,157],"lightweight":[89],"operator":[91],"offering":[92],"convolution-like":[93],"functionality,":[94],"craft":[96],"memory-efficient":[97],"CNN":[98],"(EPIM).":[103],"On":[104,140],"software":[106],"side,":[107,143],"evaluate":[109],"epitomes'":[110],"latency":[111],"and":[112,117,155],"energy":[113],"PIM-aware":[120],"layer-wise":[121],"design":[122],"method":[123],"enhance":[125],"their":[126],"hardware":[127,142],"efficiency.":[128],"We":[129],"apply":[130],"epitome-aware":[131],"quantization":[132],"epitomes.":[139],"modify":[145],"datapath":[147],"accommodate":[153],"epitomes":[154],"implement":[156],"feature":[158],"map":[159],"reuse":[160],"technique":[161],"computation":[164],"cost.":[165],"Experimental":[166],"results":[167],"reveal":[168],"our":[170],"3-bit":[171],"quantized":[172],"EPIM-ResNet50":[173],"attains":[174],"71.59%":[175],"top-1":[176],"accuracy":[177],"ImageNet,":[179],"reducing":[180],"crossbar":[181],"areas":[182],"by":[183],"30.65X.":[184],"EPIM":[185],"surpasses":[186],"state-of-the-art":[188],"pruning":[189],"methods":[190],"PIM.":[192]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
