{"id":"https://openalex.org/W7133494303","doi":"https://doi.org/10.1109/hpca68181.2026.11408436","title":"Count2Multiply: Reliable In-Memory High-Radix Counting","display_name":"Count2Multiply: Reliable In-Memory High-Radix Counting","publication_year":2026,"publication_date":"2026-01-31","ids":{"openalex":"https://openalex.org/W7133494303","doi":"https://doi.org/10.1109/hpca68181.2026.11408436"},"language":null,"primary_location":{"id":"doi:10.1109/hpca68181.2026.11408436","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpca68181.2026.11408436","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE International Symposium on High Performance Computer Architecture (HPCA)","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/A5013268618","display_name":"Jo\u00e3o Paulo C. de Lima","orcid":"https://orcid.org/0000-0001-9295-3519"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"Technische Universit\u00e4t Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Jo\u00e3o Paulo C. de Lima","raw_affiliation_strings":["TU Dresden"],"affiliations":[{"raw_affiliation_string":"TU Dresden","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128089033","display_name":"Ben Morris","orcid":null},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ben Morris","raw_affiliation_strings":["Duke University"],"affiliations":[{"raw_affiliation_string":"Duke University","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005807085","display_name":"Asif Khan","orcid":"https://orcid.org/0000-0002-5863-8467"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"Technische Universit\u00e4t Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Asif Ali Khan","raw_affiliation_strings":["TU Dresden"],"affiliations":[{"raw_affiliation_string":"TU Dresden","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030115692","display_name":"Jer\u00f3nimo Castrill\u00f3n","orcid":"https://orcid.org/0000-0002-5007-445X"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"Technische Universit\u00e4t Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jeronimo Castrillon","raw_affiliation_strings":["TU Dresden"],"affiliations":[{"raw_affiliation_string":"TU Dresden","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030875484","display_name":"Alex K. Jones","orcid":"https://orcid.org/0000-0001-7498-0206"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alex K. Jones","raw_affiliation_strings":["Syracuse University"],"affiliations":[{"raw_affiliation_string":"Syracuse University","institution_ids":["https://openalex.org/I70983195"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5013268618"],"corresponding_institution_ids":["https://openalex.org/I78650965"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.5341556,"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":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.052400000393390656,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.052400000393390656,"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"}},{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.030400000512599945,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.02810000069439411,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.35199999809265137},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.2646999955177307},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.26190000772476196},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.23100000619888306},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.21969999372959137}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4339999854564667},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31130000948905945},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.2646999955177307},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24879999458789825},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.23100000619888306},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.21969999372959137},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2125999927520752},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.20100000500679016}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hpca68181.2026.11408436","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpca68181.2026.11408436","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE International Symposium on High Performance Computer Architecture (HPCA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8973728389","display_name":null,"funder_award_id":"2534062,2450596,2511445,2328972","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W755906292","https://openalex.org/W1544481369","https://openalex.org/W1968593948","https://openalex.org/W1986431631","https://openalex.org/W2009063162","https://openalex.org/W2078640572","https://openalex.org/W2081729575","https://openalex.org/W2115157620","https://openalex.org/W2131256658","https://openalex.org/W2140975144","https://openalex.org/W2164474450","https://openalex.org/W2168116639","https://openalex.org/W2170257519","https://openalex.org/W2204664557","https://openalex.org/W2512214806","https://openalex.org/W2766890412","https://openalex.org/W2789554134","https://openalex.org/W2913174568","https://openalex.org/W2923014074","https://openalex.org/W2945951882","https://openalex.org/W2979874885","https://openalex.org/W2997394738","https://openalex.org/W2999811406","https://openalex.org/W3016765354","https://openalex.org/W3038129536","https://openalex.org/W3155004489","https://openalex.org/W3176940011","https://openalex.org/W3209244307","https://openalex.org/W3214176793","https://openalex.org/W4245698512","https://openalex.org/W4247044463","https://openalex.org/W4250945092","https://openalex.org/W4280607397","https://openalex.org/W4293812235","https://openalex.org/W4308083597","https://openalex.org/W4309620166","https://openalex.org/W4360831799","https://openalex.org/W4366668483","https://openalex.org/W4381327178","https://openalex.org/W4385964280","https://openalex.org/W4392367648","https://openalex.org/W4393407075","https://openalex.org/W4393407315","https://openalex.org/W4400985292","https://openalex.org/W4401212105","https://openalex.org/W4401567980","https://openalex.org/W4403976943"],"related_works":[],"abstract_inverted_index":{"Computing-in-memory":[0],"(CIM)":[1],"has":[2],"been":[3],"demonstrated":[4],"across":[5],"various":[6],"memory":[7,26,45],"technologies,":[8],"from":[9],"memristive":[10],"crossbars":[11],"for":[12,57],"analog":[13],"dot-products":[14],"to":[15,35,62,91,108],"large-scale":[16],"digital":[17,70],"bitwise":[18],"operations":[19,79],"in":[20,114,121],"commodity":[21,122],"DRAM":[22],"and":[23,37,59,77,106,134,145,148],"other":[24,78],"non-volatile":[25],"technologies.":[27],"However,":[28],"current":[29],"CIM":[30,39,71,116],"solutions":[31],"face":[32],"challenges":[33],"related":[34],"latency":[36,56],"reliability.":[38],"fidelity":[40],"lags":[41],"considerably":[42],"behind":[43],"standard":[44],"access":[46],"fidelity.":[47],"Furthermore,":[48],"bulkbitwise":[49],"CIM,":[50],"though":[51],"highly":[52],"parallel,":[53],"requires":[54],"long":[55],"multiplication":[58],"addition":[60],"due":[61],"bit-serial":[63],"execution.":[64],"This":[65],"paper":[66],"presents":[67],"Count2Multiply,":[68],"a":[69],"framework":[72],"that":[73],"performs":[74],"multiplication,":[75],"addition,":[76],"using":[80],"high-radix,":[81],"massively":[82],"parallel":[83],"counting":[84],"enabled":[85],"by":[86],"bulk-bitwise":[87],"inmemory":[88],"operations.":[89],"Designed":[90],"meet":[92],"fault":[93],"tolerance":[94],"requirements,":[95],"Count2Multiply":[96,120],"integrates":[97],"traditional":[98],"row-wise":[99],"error":[100,112],"correction":[101],"codes,":[102],"such":[103],"as":[104],"Hamming":[105],"BCH,":[107],"address":[109],"the":[110],"high":[111],"rates":[113],"existing":[115],"designs.":[117],"We":[118],"demonstrate":[119],"DRAMs,":[123],"achieving":[124],"on":[125],"average":[126],"1.5\u00d7":[127],"speedup,":[128],"4.6\u00d7":[129],"higher":[130],"energy":[131],"efficiency":[132,138],"(GOPS/Watt),":[133],"4.4\u00d7":[135],"better":[136],"area":[137],"(GOPS/mm<sup":[139],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[140],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>)":[141],"over":[142,152],"NVIDIA":[143],"A100;":[144],"9.7\u00d7,":[146],"8.1\u00d7,":[147],"12.9\u00d7":[149],"improvements,":[150],"respectively,":[151],"SIMDRAM.":[153]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-03-05T00:00:00"}