{"id":"https://openalex.org/W7163593328","doi":"https://doi.org/10.23919/date69613.2026.11539261","title":"Scalable Symbolic Reasoning with Matrix-Based Brain-Inspired Representations and Vector-Space Acceleration","display_name":"Scalable Symbolic Reasoning with Matrix-Based Brain-Inspired Representations and Vector-Space Acceleration","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W7163593328","doi":"https://doi.org/10.23919/date69613.2026.11539261"},"language":null,"primary_location":{"id":"doi:10.23919/date69613.2026.11539261","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date69613.2026.11539261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 Design, Automation &amp;amp; Test in Europe Conference (DATE)","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/A5137837340","display_name":"William Youngwoo Chung","orcid":null},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William Youngwoo Chung","raw_affiliation_strings":["University of California,Department of Computer Science,Irvine,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Department of Computer Science,Irvine,USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130665667","display_name":"Hyunwoo Oh","orcid":null},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hyunwoo Oh","raw_affiliation_strings":["University of California,Department of Computer Science,Irvine,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Department of Computer Science,Irvine,USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023141859","display_name":"Hamza Errahmouni Barkam","orcid":"https://orcid.org/0000-0002-0500-4647"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hamza Errahmouni Barkam","raw_affiliation_strings":["University of California,Department of Computer Science,Irvine,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Department of Computer Science,Irvine,USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034093897","display_name":"Calvin Yeung","orcid":"https://orcid.org/0009-0008-3326-8931"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Calvin Yeung","raw_affiliation_strings":["University of California,Department of Computer Science,Irvine,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Department of Computer Science,Irvine,USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5137890271","display_name":"Mohsen Imani","orcid":null},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohsen Imani","raw_affiliation_strings":["University of California,Department of Computer Science,Irvine,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Department of Computer Science,Irvine,USA","institution_ids":["https://openalex.org/I204250578"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.91953746,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"3"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13062","display_name":"Cognitive Computing and Networks","score":0.0658000037074089,"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"}},"topics":[{"id":"https://openalex.org/T13062","display_name":"Cognitive Computing and Networks","score":0.0658000037074089,"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":0.05950000137090683,"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"}},{"id":"https://openalex.org/T11431","display_name":"Action Observation and Synchronization","score":0.057100001722574234,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4341000020503998},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.4187000095844269},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.3921000063419342},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.3540000021457672},{"id":"https://openalex.org/keywords/the-symbolic","display_name":"The Symbolic","score":0.35350000858306885},{"id":"https://openalex.org/keywords/symbolic-trajectory-evaluation","display_name":"Symbolic trajectory evaluation","score":0.3328000009059906}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6164000034332275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4410000145435333},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4341000020503998},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.4187000095844269},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.40799999237060547},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.3921000063419342},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3540000021457672},{"id":"https://openalex.org/C2776095079","wikidata":"https://www.wikidata.org/wiki/Q489538","display_name":"The Symbolic","level":2,"score":0.35350000858306885},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3490999937057495},{"id":"https://openalex.org/C23123167","wikidata":"https://www.wikidata.org/wiki/Q7661193","display_name":"Symbolic trajectory evaluation","level":3,"score":0.3328000009059906},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3093999922275543},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.26179999113082886}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/date69613.2026.11539261","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date69613.2026.11539261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 Design, Automation &amp;amp; Test in Europe Conference (DATE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2070862086","https://openalex.org/W2157306293","https://openalex.org/W2908729710","https://openalex.org/W2974428947","https://openalex.org/W4210566186","https://openalex.org/W4280642803","https://openalex.org/W4312431364","https://openalex.org/W4312991481","https://openalex.org/W4388214769","https://openalex.org/W4389166754","https://openalex.org/W4397028179","https://openalex.org/W4399487929","https://openalex.org/W4411713464"],"related_works":[],"abstract_inverted_index":{"Hyperdimensional":[0],"Computing":[1],"(HDC)":[2],"enables":[3],"robust,":[4],"hardware-friendly":[5],"symbolic":[6,146],"computation,":[7],"but":[8],"mainstream":[9],"complex-valued":[10,96],"HDC":[11],"uses":[12],"commutative":[13,31],"binding":[14,32,89],"and":[15,23,44,72,90,107,131],"relies":[16],"on":[17,119],"costly":[18],"permutations":[19],"to":[20,115,143],"encode":[21],"order":[22],"directionality.":[24],"Generalized":[25],"Holographic":[26],"Reduced":[27],"Representations":[28],"(GHRR)":[29],"replace":[30],"with":[33],"non-commutative":[34],"matrix":[35,54],"multiplication,":[36],"enabling":[37],"native":[38],"encoding":[39],"of":[40],"sequences,":[41],"directed":[42],"graphs,":[43],"hierarchies":[45],"without":[46],"permutation":[47],"logic.":[48],"However,":[49],"naive":[50],"GHRR":[51,65],"incurs":[52],"prohibitive":[53],"compute/storage":[55],"overhead.":[56],"We":[57],"present":[58],"a":[59,83,94,116,140],"vector-space":[60],"flattening":[61],"method":[62],"that":[63,87],"preserves":[64],"semantics":[66],"while":[67],"executing":[68],"similarity,":[69],"training":[70],"updates,":[71],"inference":[73],"directly":[74],"using":[75],"standard":[76],"high-throughput":[77,101],"dot-product":[78],"engines.":[79],"Additionally,":[80],"we":[81],"design":[82],"custom":[84],"ASIC":[85],"accelerator":[86],"fuses":[88],"similarity":[91],"operations":[92],"into":[93],"unified":[95],"data":[97],"path,":[98],"which":[99],"supports":[100],"streaming":[102],"via":[103],"dual":[104],"DMA":[105],"engines":[106],"performs":[108],"runtime":[109],"normalization":[110],"for":[111],"accurate":[112],"inference.":[113],"Compared":[114],"PyTorch":[117],"baseline":[118],"an":[120],"NVIDIA":[121],"RTX":[122],"4090":[123],"GPU,":[124],"the":[125],"prototype":[126],"delivers":[127],"1.36\u00d7\u20131.56\u00d7":[128],"higher":[129],"throughput":[130],"achieves":[132],"16.2\u00d7\u201318.6\u00d7":[133],"better":[134],"energy":[135],"efficiency.":[136],"These":[137],"results":[138],"demonstrate":[139],"scalable":[141],"pathway":[142],"embedding":[144],"brain-inspired":[145],"reasoning":[147],"in":[148],"future":[149],"AI":[150],"accelerators.":[151]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-06-05T00:00:00"}
