{"id":"https://openalex.org/W7160927726","doi":"https://doi.org/10.48550/arxiv.2605.10612","title":"Reconfigurable Computing Challenge: Real-Time Graph Neural Networks for Online Event Selection in Big Science","display_name":"Reconfigurable Computing Challenge: Real-Time Graph Neural Networks for Online Event Selection in Big Science","publication_year":2026,"publication_date":"2026-05-11","ids":{"openalex":"https://openalex.org/W7160927726","doi":"https://doi.org/10.48550/arxiv.2605.10612"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.10612","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10612","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.10612","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135957765","display_name":"Marc Neu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Neu, Marc","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135976838","display_name":"Frank Baptist","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baptist, Frank","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135930848","display_name":"Thomas Lobmaier","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lobmaier, Thomas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135974091","display_name":"Fabio Papagno","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Papagno, Fabio","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106526226","display_name":"T. Ferber","orcid":"https://orcid.org/0000-0002-6849-0427"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ferber, Torben","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5025800213","display_name":"J\u00fcrgen Becker","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Becker, J\u00fcrgen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.6154999732971191,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.6154999732971191,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.1290999948978424,"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/T11986","display_name":"Scientific Computing and Data Management","score":0.02850000001490116,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.6294999718666077},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.5389999747276306},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5365999937057495},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4887999892234802},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.47699999809265137},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4535999894142151},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.44209998846054077},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.43309998512268066},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4269999861717224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7505999803543091},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.6294999718666077},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.5389999747276306},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5365999937057495},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4887999892234802},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.47699999809265137},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4535999894142151},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.44209998846054077},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.43309998512268066},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.4230000078678131},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3677000105381012},{"id":"https://openalex.org/C41112130","wikidata":"https://www.wikidata.org/wiki/Q2146175","display_name":"Retiming","level":2,"score":0.35190001130104065},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.34779998660087585},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.334199994802475},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3138999938964844},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3124000132083893},{"id":"https://openalex.org/C119701452","wikidata":"https://www.wikidata.org/wiki/Q5165881","display_name":"Control reconfiguration","level":2,"score":0.31189998984336853},{"id":"https://openalex.org/C19275194","wikidata":"https://www.wikidata.org/wiki/Q222903","display_name":"Multiplexing","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C112953755","wikidata":"https://www.wikidata.org/wiki/Q739462","display_name":"Graph drawing","level":3,"score":0.29269999265670776},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.28450000286102295},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27959999442100525},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.26510000228881836},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.25780001282691956},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C2779971919","wikidata":"https://www.wikidata.org/wiki/Q1378949","display_name":"Handset","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.10612","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10612","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.10612","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10612","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Graph":[0,56],"neural":[1],"networks":[2],"are":[3],"increasingly":[4],"adopted":[5],"in":[6],"trigger":[7,66],"systems":[8],"for":[9,49,59],"collider":[10],"experiments,":[11],"where":[12],"strict":[13],"latency":[14,111],"and":[15,37,76,94],"throughput":[16,101,124],"constraints":[17],"render":[18],"deployment":[19,52],"on":[20,67,154],"embedded":[21],"platforms":[22],"challenging.":[23],"As":[24],"detectors":[25],"move":[26],"towards":[27],"higher":[28],"granularity,":[29],"the":[30,50,60,68,117,142,155],"number":[31],"of":[32,53,102,112,151],"inputs":[33],"per":[34,106],"inference":[35,152],"increase":[36],"FPGA-only":[38,118],"solutions":[39],"face":[40],"resource":[41],"bottlenecks.":[42],"This":[43],"work":[44],"presents":[45],"an":[46,109,144],"end-to-end":[47,110],"demonstrator":[48],"real-time":[51,149],"a":[54,82,100,122],"dynamic":[55],"Neural":[57],"Network":[58],"Belle":[61],"II":[62],"electromagnetic":[63],"calorimeter":[64],"hardware":[65],"AMD":[69],"Versal":[70],"VCK190,":[71],"leveraging":[72],"both":[73],"FPGA":[74],"fabric":[75],"AI":[77,136],"Engine":[78,137],"tiles.":[79],"We":[80],"develop":[81],"Python-based":[83],"semi-automated":[84],"design":[85,98],"flow":[86],"covering":[87],"operator":[88],"fusion,":[89],"partitioning,":[90],"mapping,":[91],"spatial":[92],"parallelization,":[93],"kernel-level":[95],"optimization.":[96],"Our":[97],"achieves":[99],"2.94":[103],"million":[104],"events":[105],"second":[107],"at":[108,134],"7.15":[113],"microseconds.":[114],"Compared":[115],"to":[116,132],"baseline,":[119],"this":[120],"represents":[121],"53%":[123],"improvement":[125],"while":[126],"reducing":[127],"DSP":[128],"utilization":[129],"from":[130],"99%":[131],"19%":[133],"29%":[135],"tile":[138],"utilization.":[139],"To":[140],"validate":[141],"deployment,":[143],"interactive":[145],"visualization":[146],"pipeline":[147],"enables":[148],"monitoring":[150],"results":[153],"physical":[156],"demonstrator.":[157]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-13T00:00:00"}
