{"id":"https://openalex.org/W4404133681","doi":"https://doi.org/10.1145/3649329.3655930","title":"Addition is Most You Need: Efficient Floating-Point SRAM Compute-in-Memory by Harnessing Mantissa Addition","display_name":"Addition is Most You Need: Efficient Floating-Point SRAM Compute-in-Memory by Harnessing Mantissa Addition","publication_year":2024,"publication_date":"2024-06-23","ids":{"openalex":"https://openalex.org/W4404133681","doi":"https://doi.org/10.1145/3649329.3655930"},"language":"en","primary_location":{"id":"doi:10.1145/3649329.3655930","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3649329.3655930","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3649329.3655930?download=true","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://dl.acm.org/doi/pdf/10.1145/3649329.3655930?download=true","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062801966","display_name":"Weidong Cao","orcid":"https://orcid.org/0000-0001-7539-8250"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Weidong Cao","raw_affiliation_strings":["The George Washington University, Washington, DC, United States"],"affiliations":[{"raw_affiliation_string":"The George Washington University, Washington, DC, United States","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113218959","display_name":"Jian Gao","orcid":"https://orcid.org/0009-0001-4757-5376"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jian Gao","raw_affiliation_strings":["Northeastern University, Boston, MA, United States"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, United States","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103105426","display_name":"Xin Xin","orcid":"https://orcid.org/0000-0003-0952-2115"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Xin","raw_affiliation_strings":["University of Central Florida, Orlando, FL, United States"],"affiliations":[{"raw_affiliation_string":"University of Central Florida, Orlando, FL, United States","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010392575","display_name":"Xuan Zhang","orcid":"https://orcid.org/0000-0002-0482-5435"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuan Zhang","raw_affiliation_strings":["Northeastern University, Boston, MA, United States"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, United States","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5062801966"],"corresponding_institution_ids":["https://openalex.org/I193531525"],"apc_list":null,"apc_paid":null,"fwci":1.0229,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.77437882,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"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/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T10502","display_name":"Advanced Memory and Neural Computing","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/T10363","display_name":"Low-power high-performance VLSI design","score":0.9987999796867371,"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/static-random-access-memory","display_name":"Static random-access memory","score":0.8367654085159302},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6455252170562744},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.6165341138839722},{"id":"https://openalex.org/keywords/random-access-memory","display_name":"Random access memory","score":0.5771751403808594},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4828244149684906},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.25326934456825256},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09632781147956848}],"concepts":[{"id":"https://openalex.org/C68043766","wikidata":"https://www.wikidata.org/wiki/Q267416","display_name":"Static random-access memory","level":2,"score":0.8367654085159302},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6455252170562744},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.6165341138839722},{"id":"https://openalex.org/C2994168587","wikidata":"https://www.wikidata.org/wiki/Q5295","display_name":"Random access memory","level":2,"score":0.5771751403808594},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4828244149684906},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.25326934456825256},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09632781147956848},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3649329.3655930","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3649329.3655930","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3649329.3655930?download=true","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:10.1145/3649329.3655930","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3649329.3655930","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3649329.3655930?download=true","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","display_name":"Affordable and clean energy","score":0.6000000238418579}],"awards":[{"id":"https://openalex.org/G8619384459","display_name":null,"funder_award_id":"1942900","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4404133681.pdf","grobid_xml":"https://content.openalex.org/works/W4404133681.grobid-xml"},"referenced_works_count":10,"referenced_works":["https://openalex.org/W2526202524","https://openalex.org/W2949989598","https://openalex.org/W3033443178","https://openalex.org/W3036079062","https://openalex.org/W3211168157","https://openalex.org/W4233429846","https://openalex.org/W4285676450","https://openalex.org/W4302391768","https://openalex.org/W4384947654","https://openalex.org/W4388692445"],"related_works":["https://openalex.org/W1909296377","https://openalex.org/W2089002058","https://openalex.org/W3185029353","https://openalex.org/W2969498307","https://openalex.org/W3116379964","https://openalex.org/W2915176329","https://openalex.org/W2793465010","https://openalex.org/W2208608937","https://openalex.org/W2120018824","https://openalex.org/W2766443086"],"abstract_inverted_index":{"The":[0],"compute-in-memory":[1],"(CIM)":[2],"paradigm":[3],"holds":[4],"great":[5,199],"promise":[6],"to":[7,56,114,146,188],"efficiently":[8],"accelerate":[9],"machine":[10],"learning":[11],"workloads.":[12],"Among":[13],"memory":[14,18],"devices,":[15],"static":[16],"random-access":[17],"(SRAM)":[19],"stands":[20],"out":[21],"as":[22],"a":[23,41,83,140,189],"practical":[24],"choice":[25],"for":[26,74,126,201],"its":[27,172,198],"exceptional":[28],"reliability":[29],"in":[30,44,60,151,175,184],"the":[31,79,115,127,152,157,168],"digital":[32,153,191],"domain":[33,154],"and":[34,63,98],"excellent":[35],"scalability.":[36],"Recently,":[37],"there":[38],"has":[39],"been":[40],"growing":[42],"interest":[43],"accelerating":[45],"floating-point":[46],"(FP)":[47],"deep":[48],"neural":[49],"networks":[50],"(DNNs)":[51],"with":[52,167],"SRAM":[53,71,143],"CIM":[54,72,144],"due":[55],"their":[57],"critical":[58],"importance":[59],"DNN":[61,203],"training":[62],"high-accurate":[64],"inference.":[65],"This":[66],"paper":[67],"proposes":[68],"an":[69],"energy-efficient":[70],"macro":[73,145],"FP":[75,89,118,130,202],"DNNs.":[76],"To":[77],"achieve":[78],"design,":[80],"we":[81,138],"identify":[82],"lightweight":[84],"approach":[85],"that":[86,105],"decomposes":[87],"conventional":[88],"mantissa":[90,95,99,107,121,149,161],"multiplication":[91],"into":[92],"two":[93],"parts:":[94],"sub-addition":[96],"(sub-ADD)":[97],"sub-multiplication":[100],"(sub-MUL).":[101],"Our":[102],"study":[103],"shows":[104],"while":[106,155],"sub-MUL":[108,162],"is":[109,134],"compute-intensive,":[110],"it":[111],"only":[112],"contributes":[113],"minority":[116],"of":[117,129,160],"products,":[119],"whereas":[120],"sub-ADD,":[122],"although":[123],"compute-light,":[124],"accounts":[125],"majority":[128],"products.":[131],"Recognizing":[132],"\"Addition":[133],"Most":[135],"You":[136],"Need\",":[137],"develop":[139],"novel":[141],"hybrid-domain":[142],"accurately":[147],"handle":[148],"sub-ADD":[150],"improving":[156],"energy":[158,176],"efficiency":[159,177],"using":[163],"analog":[164],"computing.":[165],"Experiments":[166],"MLPerf":[169],"benchmark":[170],"show":[171],"remarkable":[173],"improvement":[174],"on":[178],"average":[179],"by":[180],"3\u00d7~":[181],"3.6\u00d7":[182],"(2.5\u00d7~3.1\u00d7)":[183],"inference":[185],"(training)":[186],"compared":[187],"fully":[190],"baseline":[192],"without":[193],"any":[194],"accuracy":[195],"loss,":[196],"showcasing":[197],"potential":[200],"acceleration.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}