{"id":"https://openalex.org/W4414198065","doi":"https://doi.org/10.1109/dac63849.2025.11133088","title":"NSFlow: An End-to-End FPGA Framework with Scalable Dataflow Architecture for Neuro-Symbolic AI","display_name":"NSFlow: An End-to-End FPGA Framework with Scalable Dataflow Architecture for Neuro-Symbolic AI","publication_year":2025,"publication_date":"2025-06-22","ids":{"openalex":"https://openalex.org/W4414198065","doi":"https://doi.org/10.1109/dac63849.2025.11133088"},"language":"en","primary_location":{"id":"doi:10.1109/dac63849.2025.11133088","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dac63849.2025.11133088","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 62nd ACM/IEEE Design Automation Conference (DAC)","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/A5102786052","display_name":"Hanchen Yang","orcid":"https://orcid.org/0009-0005-6074-8357"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hanchen Yang","raw_affiliation_strings":["Georgia Institute of Technology,Atlanta,GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,Atlanta,GA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076856438","display_name":"Zishen Wan","orcid":"https://orcid.org/0000-0002-2982-5351"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zishen Wan","raw_affiliation_strings":["Georgia Institute of Technology,Atlanta,GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,Atlanta,GA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078314931","display_name":"Ritik Raj","orcid":"https://orcid.org/0009-0005-1853-6107"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ritik Raj","raw_affiliation_strings":["Georgia Institute of Technology,Atlanta,GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,Atlanta,GA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042175526","display_name":"Joongun Park","orcid":"https://orcid.org/0009-0000-8406-0817"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joongun Park","raw_affiliation_strings":["Georgia Institute of Technology,Atlanta,GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,Atlanta,GA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100424999","display_name":"Ziwei Li","orcid":"https://orcid.org/0000-0002-7631-989X"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ziwei Li","raw_affiliation_strings":["Georgia Institute of Technology,Atlanta,GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,Atlanta,GA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007782265","display_name":"Ananda Samajdar","orcid":"https://orcid.org/0000-0003-0046-3745"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ananda Samajdar","raw_affiliation_strings":["IBM Research,Yorktown Heights,NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research,Yorktown Heights,NY","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091408102","display_name":"Arijit Raychowdhury","orcid":"https://orcid.org/0000-0001-8391-0576"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arijit Raychowdhury","raw_affiliation_strings":["Georgia Institute of Technology,Atlanta,GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,Atlanta,GA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034089074","display_name":"Tushar Krishna","orcid":"https://orcid.org/0000-0001-5738-6942"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tushar Krishna","raw_affiliation_strings":["Georgia Institute of Technology,Atlanta,GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,Atlanta,GA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5102786052"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":1.7031,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.85973919,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9947999715805054,"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":0.9947999715805054,"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/T10320","display_name":"Neural Networks and Applications","score":0.989300012588501,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9832000136375427,"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/speedup","display_name":"Speedup","score":0.7684000134468079},{"id":"https://openalex.org/keywords/dataflow","display_name":"Dataflow","score":0.7495999932289124},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6798999905586243},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6241999864578247},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.5723999738693237},{"id":"https://openalex.org/keywords/dataflow-architecture","display_name":"Dataflow architecture","score":0.46369999647140503},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.4544000029563904},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.3402000069618225}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7946000099182129},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.7684000134468079},{"id":"https://openalex.org/C96324660","wikidata":"https://www.wikidata.org/wiki/Q205446","display_name":"Dataflow","level":2,"score":0.7495999932289124},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6798999905586243},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6241999864578247},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.5723999738693237},{"id":"https://openalex.org/C176727019","wikidata":"https://www.wikidata.org/wiki/Q1172415","display_name":"Dataflow architecture","level":3,"score":0.46369999647140503},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.4544000029563904},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.4480000138282776},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3978999853134155},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3328999876976013},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.32820001244544983},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30000001192092896},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C37724790","wikidata":"https://www.wikidata.org/wiki/Q210813","display_name":"Direct memory access","level":3,"score":0.29260000586509705},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.2782999873161316},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.27219998836517334},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25850000977516174},{"id":"https://openalex.org/C157170001","wikidata":"https://www.wikidata.org/wiki/Q4781507","display_name":"Applications of artificial intelligence","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25589999556541443},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.2515999972820282},{"id":"https://openalex.org/C133875982","wikidata":"https://www.wikidata.org/wiki/Q764810","display_name":"Shared memory","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dac63849.2025.11133088","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dac63849.2025.11133088","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 62nd ACM/IEEE Design Automation Conference (DAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306087","display_name":"Semiconductor Research Corporation","ror":"https://ror.org/047z4n946"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2107647130","https://openalex.org/W2625954420","https://openalex.org/W2794754997","https://openalex.org/W2963690694","https://openalex.org/W3001663911","https://openalex.org/W3017521908","https://openalex.org/W3035674654","https://openalex.org/W3092731680","https://openalex.org/W3097528158","https://openalex.org/W3117577445","https://openalex.org/W3130920634","https://openalex.org/W3132745255","https://openalex.org/W3176187895","https://openalex.org/W4213454368","https://openalex.org/W4308939312","https://openalex.org/W4360977202","https://openalex.org/W4390940921","https://openalex.org/W4393578447","https://openalex.org/W4393578753","https://openalex.org/W4393949386","https://openalex.org/W4400681438","https://openalex.org/W4401568544","https://openalex.org/W4402364428","https://openalex.org/W4402592760","https://openalex.org/W4404102073","https://openalex.org/W4405909140","https://openalex.org/W4409248730"],"related_works":[],"abstract_inverted_index":{"Neuro-Symbolic":[0],"AI":[1,24],"(NSAI)":[2],"is":[3,219],"an":[4,115],"emerging":[5],"paradigm":[6],"that":[7,136],"integrates":[8],"neural":[9],"networks":[10],"with":[11,89,152,199],"symbolic":[12,206],"reasoning":[13,18,38],"to":[14,33,61,106,120,223],"enhance":[15],"the":[16,96,213,220],"transparency,":[17],"capabilities,":[19],"and":[20,40,69,84,101,125,141,158,186],"data":[21,139],"efficiency":[22],"of":[23,215],"systems.":[25,129,237],"Recent":[26],"NSAI":[27,49,76,107,128,163,227],"systems":[28],"have":[29],"gained":[30],"traction":[31],"due":[32,60],"their":[34,62],"exceptional":[35],"performance":[36],"in":[37,81],"tasks":[39,50],"human-AI":[41],"collaborative":[42],"scenarios.":[43],"Despite":[44],"these":[45],"algorithmic":[46],"advancements,":[47],"executing":[48],"on":[51],"existing":[52,90],"hardware":[53],"(e.g.,":[54],"CPUs,":[55],"GPUs,":[56],"TPUs)":[57],"remains":[58],"challenging,":[59],"heterogeneous":[63],"computing":[64],"kernels,":[65],"high":[66,122],"memory":[67,71],"intensity,":[68],"unique":[70],"access":[72],"patterns.":[73],"Moreover,":[74],"current":[75],"algorithms":[77,228],"exhibit":[78],"significant":[79],"variation":[80],"operation":[82],"types":[83],"scales,":[85],"making":[86],"them":[87],"incompatible":[88],"ML":[91],"accelerators.":[92],"These":[93],"challenges":[94],"highlight":[95],"need":[97],"for":[98,234],"a":[99,132,149,231],"versatile":[100],"flexible":[102,153],"acceleration":[103,117],"framework":[104,118,222],"tailored":[105],"workloads.":[108],"In":[109],"this":[110],"paper,":[111],"we":[112],"propose":[113],"NSFlow,":[114],"FPGA-based":[116],"designed":[119],"achieve":[121],"efficiency,":[123],"scalability,":[124,198],"versatility":[126],"across":[127,162],"NSFlow":[130,165,194,218],"features":[131],"design":[133],"architecture":[134],"generator":[135],"identifies":[137],"workload":[138],"dependencies":[140],"creates":[142],"optimized":[143],"dataflow":[144],"architectures,":[145],"as":[146,148],"well":[147],"reconfigurable":[150],"array":[151],"compute":[154],"units,":[155],"re-organizable":[156],"memory,":[157],"mixed-precision":[159],"capabilities.":[160],"Evaluating":[161],"workloads,":[164],"achieves":[166],"$31":[167],"\\times$":[168,176,180,190,202],"speedup":[169,181],"over":[170,177,182,191],"Jetson":[171],"TX2,":[172],"more":[173,187],"than":[174,188],"$2":[175],"GPU,":[178],"$8":[179],"TPU-like":[183],"systolic":[184],"array,":[185],"$3":[189],"Xilinx":[192],"DPU.":[193],"also":[195],"demonstrates":[196],"enhanced":[197],"only":[200],"$4":[201],"runtime":[203],"increase":[204],"when":[205],"workloads":[207],"scale":[208],"by":[209],"$150":[210],"\\times$.":[211],"To":[212],"best":[214],"our":[216],"knowledge,":[217],"first":[221],"enable":[224],"real-time":[225],"generalizable":[226],"acceleration,":[229],"demonstrating":[230],"promising":[232],"solution":[233],"next-generation":[235],"cognitive":[236]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-28T09:10:13.091523","created_date":"2025-10-10T00:00:00"}