{"id":"https://openalex.org/W7164126126","doi":"https://doi.org/10.1109/fccm68464.2026.00028","title":"VSALUT: A Lightweight Low-Dimensional VSA Classifier for Efficient Inference on FPGA","display_name":"VSALUT: A Lightweight Low-Dimensional VSA Classifier for Efficient Inference on FPGA","publication_year":2026,"publication_date":"2026-05-13","ids":{"openalex":"https://openalex.org/W7164126126","doi":"https://doi.org/10.1109/fccm68464.2026.00028"},"language":null,"primary_location":{"id":"doi:10.1109/fccm68464.2026.00028","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fccm68464.2026.00028","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 34th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)","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/A5003266673","display_name":"Nuntipat Narkthong","orcid":"https://orcid.org/0009-0002-1648-3142"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]},{"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":"Nuntipat Narkthong","raw_affiliation_strings":["Northeastern University,Boston,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,Boston,USA","institution_ids":["https://openalex.org/I12912129","https://openalex.org/I111088046"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5138384416","display_name":"Xiaolin Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]},{"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":"Xiaolin Xu","raw_affiliation_strings":["Northeastern University,Boston,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,Boston,USA","institution_ids":["https://openalex.org/I12912129","https://openalex.org/I111088046"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":0.93254479,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"119","last_page":"123"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.5257999897003174,"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":0.5257999897003174,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.05260000005364418,"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/T10904","display_name":"Embedded Systems Design Techniques","score":0.04100000113248825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5616999864578247},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5105000138282776},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.45669999718666077},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3181999921798706},{"id":"https://openalex.org/keywords/fuzzy-inference-system","display_name":"Fuzzy inference system","score":0.2827000021934509}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6998999714851379},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5616999864578247},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.531000018119812},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5105000138282776},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.45669999718666077},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3181999921798706},{"id":"https://openalex.org/C2987376176","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy inference system","level":5,"score":0.2827000021934509},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2653999924659729},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.24770000576972961}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fccm68464.2026.00028","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fccm68464.2026.00028","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 34th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":20,"referenced_works":["https://openalex.org/W2070862086","https://openalex.org/W2112796928","https://openalex.org/W2296509296","https://openalex.org/W2565125333","https://openalex.org/W2907163239","https://openalex.org/W2951537853","https://openalex.org/W2990838824","https://openalex.org/W3093982621","https://openalex.org/W3158860039","https://openalex.org/W3159008243","https://openalex.org/W3183144345","https://openalex.org/W3214202924","https://openalex.org/W4391455313","https://openalex.org/W4394998755","https://openalex.org/W4401935097","https://openalex.org/W4403278560","https://openalex.org/W4403278591","https://openalex.org/W4406092772","https://openalex.org/W4407953506","https://openalex.org/W4410810291"],"related_works":[],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"(DNNs)":[3],"have":[4],"achieved":[5],"remarkable":[6],"success":[7],"in":[8,18],"various":[9],"domains.":[10],"However,":[11],"their":[12,25],"deployment":[13],"on":[14,65,101,141],"resource-constrained":[15],"devices":[16],"and":[17,28,90,97,118,126],"ultra-low-latency":[19],"scenarios":[20],"remains":[21],"challenging":[22],"due":[23],"to":[24,54,78,85,94,106],"substantial":[26],"computational":[27],"memory":[29],"requirements.":[30],"This":[31,129],"paper":[32],"proposes":[33],"leveraging":[34],"the":[35,44,87],"low-dimensional":[36,41],"computing":[37],"(LDC)":[38],"classifier,":[39,49],"a":[40,51,69,82,91,132],"variant":[42],"of":[43],"vector":[45],"symbolic":[46],"architecture":[47],"(VSA)":[48],"as":[50],"lightweight":[52,139],"alternative":[53],"DNNs.":[55,128],"We":[56],"introduce":[57],"VSALUT,":[58],"an":[59,74],"open-source":[60],"framework":[61],"for":[62,137],"implementing":[63],"LDC":[64],"FPGAs.":[66],"VSALUT":[67,113],"employs":[68],"lookup":[70],"table":[71],"(LUT)-based":[72],"architecture,":[73],"approximate":[75],"encoding":[76],"scheme":[77],"replace":[79],"complex":[80],"adders,":[81],"pruning":[83],"strategy":[84],"reduce":[86],"model\u2019s":[88],"size,":[89],"pipelining":[92],"technique":[93],"maximize":[95],"performance":[96],"resource":[98],"efficiency.":[99],"Evaluation":[100],"five":[102],"datasets,":[103],"commonly":[104],"used":[105],"evaluate":[107],"ultra-low":[108],"latency":[109,119],"architectures,":[110],"demonstrates":[111],"that":[112],"achieves":[114],"significant":[115],"hardware":[116],"size":[117],"reductions":[120],"over":[121],"existing":[122],"LDC,":[123],"high-dimensional":[124],"VSA,":[125],"LUT-based":[127],"work":[130],"establishes":[131],"promising":[133],"new":[134],"research":[135],"direction":[136],"ultra-low-latency,":[138],"inference":[140],"FPGAs":[142],"using":[143],"LDC.":[144]},"counts_by_year":[],"updated_date":"2026-06-12T06:20:11.936012","created_date":"2026-06-11T00:00:00"}