{"id":"https://openalex.org/W7165733020","doi":"https://doi.org/10.48550/arxiv.2606.24417","title":"cuSBF: A Minimizer-Aware Bloom Filter for Genomic Sequence Data on Modern GPUs","display_name":"cuSBF: A Minimizer-Aware Bloom Filter for Genomic Sequence Data on Modern GPUs","publication_year":2026,"publication_date":"2026-06-23","ids":{"openalex":"https://openalex.org/W7165733020","doi":"https://doi.org/10.48550/arxiv.2606.24417"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.24417","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24417","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.24417","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139290845","display_name":"Tim Dortmann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dortmann, Tim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044779204","display_name":"Markus Vieth","orcid":"https://orcid.org/0000-0003-1707-6231"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vieth, Markus","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5020388832","display_name":"Bertil Schmidt","orcid":"https://orcid.org/0000-0003-2597-8331"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schmidt, Bertil","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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/T11478","display_name":"Caching and Content Delivery","score":0.7210000157356262,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11478","display_name":"Caching and Content Delivery","score":0.7210000157356262,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.04039999842643738,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"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"}},{"id":"https://openalex.org/T12326","display_name":"Network Packet Processing and Optimization","score":0.03909999877214432,"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/bloom-filter","display_name":"Bloom filter","score":0.932200014591217},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7013999819755554},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6773999929428101},{"id":"https://openalex.org/keywords/memory-footprint","display_name":"Memory footprint","score":0.673799991607666},{"id":"https://openalex.org/keywords/cuda","display_name":"CUDA","score":0.542900025844574},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.49810001254081726},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.420199990272522},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.4178999960422516},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4065999984741211}],"concepts":[{"id":"https://openalex.org/C147224247","wikidata":"https://www.wikidata.org/wiki/Q885373","display_name":"Bloom filter","level":2,"score":0.932200014591217},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8258000016212463},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.7529000043869019},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7013999819755554},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6773999929428101},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.673799991607666},{"id":"https://openalex.org/C2778119891","wikidata":"https://www.wikidata.org/wiki/Q477690","display_name":"CUDA","level":2,"score":0.542900025844574},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.49810001254081726},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.420199990272522},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4178999960422516},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4065999984741211},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.3589000105857849},{"id":"https://openalex.org/C50630238","wikidata":"https://www.wikidata.org/wiki/Q971505","display_name":"General-purpose computing on graphics processing units","level":3,"score":0.35370001196861267},{"id":"https://openalex.org/C202491316","wikidata":"https://www.wikidata.org/wiki/Q272683","display_name":"Instruction set","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.35089999437332153},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.3418999910354614},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.32249999046325684},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.30799999833106995},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30570000410079956},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C2781357197","wikidata":"https://www.wikidata.org/wiki/Q5757597","display_name":"High memory","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C19275194","wikidata":"https://www.wikidata.org/wiki/Q222903","display_name":"Multiplexing","level":2,"score":0.2874999940395355}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.24417","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24417","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.24417","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24417","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5190361142158508}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Efficient":[0],"genomic":[1,107,237],"k-mer":[2],"indexing":[3],"depends":[4],"on":[5,109,179],"approximate":[6],"membership":[7],"query":[8],"(AMQ)":[9],"structures":[10],"that":[11,77,226],"must":[12],"deliver":[13],"high":[14,52],"throughput,":[15],"low":[16],"false-positive":[17],"rates":[18],"(FPR),":[19],"and":[20,37,59,94,114,146,155],"modest":[21],"memory":[22,61,209],"footprints.":[23],"The":[24],"Super":[25,162],"Bloom":[26,137,163],"filter":[27,138],"(SBF)":[28],"is":[29,232],"attractive":[30],"for":[31,80,144,148,197,221],"this":[32],"scenario":[33],"because":[34],"minimizer-guided":[35],"sharding":[36],"the":[38,42,119,128,134,159,233],"Findere":[39],"scheme":[40],"exploit":[41],"redundancy":[43],"of":[44],"overlapping":[45],"k-mers.":[46],"However,":[47],"those":[48],"same":[49],"features":[50],"cause":[51],"per-k-mer":[53],"compute":[54],"cost,":[55],"severe":[56],"register":[57],"pressure,":[58],"irregular":[60],"accesses,":[62],"which":[63],"hinder":[64],"an":[65,72],"effective":[66],"GPU":[67,103],"implementation.":[68,165],"We":[69],"present":[70],"cuSBF,":[71],"open-source,":[73],"header-only":[74],"CUDA":[75],"library":[76],"implements":[78],"SBF":[79],"sequence-native":[81],"workloads.":[82],"cuSBF's":[83,212],"design":[84,214],"merges":[85],"sectorized":[86],"shards,":[87],"cooperative":[88],"shared-memory":[89],"tiling,":[90],"warp-level":[91],"shard":[92],"sharing,":[93],"segmented":[95],"warp":[96],"reductions,":[97],"turning":[98],"super-k-mer":[99],"locality":[100],"into":[101],"scalable":[102],"parallelism.":[104],"Across":[105],"real":[106],"workloads":[108],"RTX":[110,129],"PRO":[111,130],"6000":[112],"Blackwell":[113],"GH200":[115],"systems,":[116],"cuSBF":[117],"achieves":[118],"highest":[120],"throughput":[121],"among":[122],"all":[123],"evaluated":[124],"sequence-capable":[125],"baselines.":[126],"On":[127],"6000,":[131],"it":[132],"surpasses":[133],"cuCollections":[135,206],"blocked":[136],"baseline":[139],"by":[140,176],"up":[141,152],"to":[142,153,235],"9.1x":[143],"insertion":[145],"7.7x":[147],"query,":[149],"while":[150],"reaching":[151],"92x":[154],"234x":[156],"speedups":[157],"over":[158],"multi-threaded":[160],"CPU":[161],"reference":[164],"It":[166],"also":[167],"outperforms":[168],"GPU-based":[169],"dynamic":[170],"AMQs":[171],"(Cuckoo,":[172],"Two-Choice,":[173],"Quotient":[174],"filters)":[175],"1.5-3400x":[177],"depending":[178],"workload":[180],"characteristics.":[181],"A":[182],"parameter":[183],"sweep":[184],"identifies":[185],"(s":[186],"=":[187,190,193,199],"28,":[188],"m":[189],"16,":[191],"H":[192],"4)":[194],"as":[195],"Pareto-optimal":[196],"k":[198],"31,":[200],"yielding":[201],"significantly":[202],"lower":[203],"FPR":[204],"than":[205],"at":[207],"matched":[208],"budgets.":[210],"Crucially,":[211],"architecture-aware":[213],"sustains":[215],"85%":[216],"streaming":[217],"multiprocessor":[218],"utilization":[219],"even":[220],"out-of-cache":[222],"filters":[223],"-":[224],"proving":[225],"sequence":[227],"locality,":[228],"not":[229],"raw":[230],"bandwidth,":[231],"key":[234],"GPU-accelerated":[236],"indexing.":[238]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-25T00:00:00"}