{"id":"https://openalex.org/W3173736108","doi":"https://doi.org/10.1145/3453688.3461494","title":"Re2PIM","display_name":"Re2PIM","publication_year":2021,"publication_date":"2021-06-18","ids":{"openalex":"https://openalex.org/W3173736108","doi":"https://doi.org/10.1145/3453688.3461494","mag":"3173736108"},"language":"en","primary_location":{"id":"doi:10.1145/3453688.3461494","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3453688.3461494","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 Great Lakes Symposium on VLSI","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/A5101870121","display_name":"Yilong Zhao","orcid":"https://orcid.org/0000-0002-4888-9027"},"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":"Yilong Zhao","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","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, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045693138","display_name":"Naifeng Jing","orcid":"https://orcid.org/0000-0001-8417-5796"},"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":"Naifeng Jing","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056632010","display_name":"Xiaoyao Liang","orcid":"https://orcid.org/0000-0002-2790-5884"},"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":"Xiaoyao Liang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053801300","display_name":"Li Jiang","orcid":"https://orcid.org/0000-0002-7353-8798"},"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":"Li Jiang","raw_affiliation_strings":["Shanghai Jiao Tong University & Shanghai Qi Zhi Institute, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University & Shanghai Qi Zhi Institute, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101870121"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.2005,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.4963236,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"15","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.6860872507095337},{"id":"https://openalex.org/keywords/resistive-random-access-memory","display_name":"Resistive random-access memory","score":0.6564146280288696},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.5788362622261047},{"id":"https://openalex.org/keywords/matrix-multiplication","display_name":"Matrix multiplication","score":0.5322563052177429},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.5106173157691956},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.474016010761261},{"id":"https://openalex.org/keywords/dot-product","display_name":"Dot product","score":0.4583539068698883},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43071362376213074},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.42754867672920227},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.4261529743671417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18094441294670105},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.15439856052398682},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.13692554831504822},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.08550837635993958},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07807978987693787}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6860872507095337},{"id":"https://openalex.org/C182019814","wikidata":"https://www.wikidata.org/wiki/Q1143830","display_name":"Resistive random-access memory","level":3,"score":0.6564146280288696},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.5788362622261047},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.5322563052177429},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.5106173157691956},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.474016010761261},{"id":"https://openalex.org/C32900221","wikidata":"https://www.wikidata.org/wiki/Q181365","display_name":"Dot product","level":2,"score":0.4583539068698883},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43071362376213074},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.42754867672920227},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.4261529743671417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18094441294670105},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.15439856052398682},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.13692554831504822},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.08550837635993958},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07807978987693787},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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:10.1145/3453688.3461494","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3453688.3461494","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 Great Lakes Symposium on VLSI","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.9100000262260437,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G6307311650","display_name":null,"funder_award_id":"61772331, 61834006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1905882502","https://openalex.org/W2008311222","https://openalex.org/W2162279286","https://openalex.org/W2194775991","https://openalex.org/W2508602506","https://openalex.org/W2518281301","https://openalex.org/W2612375349","https://openalex.org/W2612445135","https://openalex.org/W2618530766","https://openalex.org/W2725159389","https://openalex.org/W2913347945","https://openalex.org/W2946522000","https://openalex.org/W2962835968","https://openalex.org/W2963341956","https://openalex.org/W2970971581","https://openalex.org/W2979663695","https://openalex.org/W2997273453","https://openalex.org/W3023950925","https://openalex.org/W3042493405","https://openalex.org/W4243519499","https://openalex.org/W4254672563","https://openalex.org/W4295312788"],"related_works":["https://openalex.org/W2047588290","https://openalex.org/W1970548269","https://openalex.org/W1543798151","https://openalex.org/W2622518229","https://openalex.org/W2380696053","https://openalex.org/W1832263773","https://openalex.org/W2107242824","https://openalex.org/W2292897598","https://openalex.org/W2619946702","https://openalex.org/W3173736108"],"abstract_inverted_index":{"ReRAM-based":[0,35,98],"deep":[1],"neural":[2],"network":[3],"(DNN)":[4],"accelerator":[5],"shows":[6],"enormous":[7],"potential":[8],"because":[9],"of":[10,19,49,66,84,103,107,133],"ReRAM's":[11],"high":[12,146],"computational-density":[13],"and":[14,30,54,130,166,172],"power-efficiency.":[15],"A":[16],"typical":[17],"feature":[18],"DNNs":[20,29],"is":[21,70,105],"that":[22,161],"weight":[23,140],"matrix":[24],"size":[25],"varies":[26],"across":[27],"diverse":[28],"DNN":[31,36,99,153,158],"layers.":[32],"However,":[33],"current":[34],"accelerators":[37,180],"adopt":[38],"a":[39,47,96,145],"fixed-sized":[40],"compute":[41],"unit":[42],"(CU)":[43],"design,":[44],"resulting":[45],"in":[46,169],"dilemma":[48],"trading":[50],"off":[51],"between":[52],"throughput":[53,150,174],"energy-efficiency:":[55],"when":[56,73],"computing":[57,74],"large":[58,79],"vector-matrix":[59,76],"multiplication":[60,77],"with":[61,78],"small":[62,75],"CUs,":[63,80],"the":[64,67,81,88,138,178],"overhead":[65],"peripheral":[68],"circuits":[69],"relatively":[71],"high;":[72],"low":[82],"utilization":[83],"ReRAM":[85],"crossbars":[86],"damages":[87],"throughput.":[89],"In":[90],"this":[91],"work,":[92],"we":[93],"propose":[94],"Re2PIM,":[95],"reconfigurable":[97,108],"accelerator.":[100],"Each":[101],"tile":[102],"Re2PIM":[104,162],"composed":[106],"units":[109],"(RUs),":[110],"which":[111],"can":[112,127,163],"be":[113],"reconfigured":[114],"as":[115],"vector-vatrix":[116],"multiplier":[117],"(VMM),":[118],"digital-to-analog":[119],"converter":[120],"(DAC),":[121],"or":[122],"analog":[123],"shift-and-add":[124],"(AS+A).":[125],"We":[126],"reconfigure":[128],"RUs":[129],"obtain":[131],"CUs":[132],"various":[134,152],"sizes":[135],"according":[136],"to":[137,177],"DNN's":[139],"matrices.":[141],"It":[142],"hence":[143],"assures":[144],"energy-efficiency":[147],"without":[148],"damaging":[149],"given":[151],"benchmarks.":[154],"Evaluations":[155],"on":[156],"different":[157],"benchmarks":[159],"show":[160],"achieve":[164],"27\u00d7/34\u00d7/1.5\u00d7":[165],"5.7\u00d7/17\u00d7/8.2\u00d7":[167],"improvement":[168],"energy":[170],"efficiency":[171],"computational":[173],"respectively":[175],"compared":[176],"state-of-art":[179],"(PRIME":[181],"/":[182,184],"ISAAC":[183],"TIMELY).":[185]},"counts_by_year":[{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2021-07-05T00:00:00"}