{"id":"https://openalex.org/W7154986773","doi":"https://doi.org/10.48550/arxiv.2604.15768","title":"A Fully GPU-Accelerated Framework for High-Performance Configuration Interaction Selection with Neural Network Quantum States","display_name":"A Fully GPU-Accelerated Framework for High-Performance Configuration Interaction Selection with Neural Network Quantum States","publication_year":2026,"publication_date":"2026-04-17","ids":{"openalex":"https://openalex.org/W7154986773","doi":"https://doi.org/10.48550/arxiv.2604.15768"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.15768","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15768","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.2604.15768","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134018791","display_name":"Daran Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Daran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088984005","display_name":"Bowen Kan","orcid":"https://orcid.org/0009-0001-6951-7193"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kan, Bowen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130123241","display_name":"Haoquan Long","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Long, Haoquan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087484624","display_name":"Hairui Zhao","orcid":"https://orcid.org/0009-0008-7081-5172"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Hairui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134041055","display_name":"Haoxu Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Haoxu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134032706","display_name":"Yicheng Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yicheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134010396","display_name":"Pengyu Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Pengyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134080092","display_name":"Ankang Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng, Ankang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134083783","display_name":"Wenjing Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Wenjing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123337664","display_name":"Yida Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Yida","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134082172","display_name":"Zhenyu Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zhenyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134041651","display_name":"Honghui Shang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shang, Honghui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134037643","display_name":"Yunquan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yunquan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063703614","display_name":"Dingwen Tao","orcid":"https://orcid.org/0000-0001-5422-4497"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao, Dingwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134061905","display_name":"Ninghui Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Ninghui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134079977","display_name":"Guangming Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Guangming","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/T11948","display_name":"Machine Learning in Materials Science","score":0.8199999928474426,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.8199999928474426,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11804","display_name":"Quantum many-body systems","score":0.06260000169277191,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.014000000432133675,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.7627000212669373},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7224000096321106},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6668000221252441},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5454000234603882},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5367000102996826},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.4438000023365021},{"id":"https://openalex.org/keywords/cuda","display_name":"CUDA","score":0.3370000123977661}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7792999744415283},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7627000212669373},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7224000096321106},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6668000221252441},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5906000137329102},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5738000273704529},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5454000234603882},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5367000102996826},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.4438000023365021},{"id":"https://openalex.org/C2778119891","wikidata":"https://www.wikidata.org/wiki/Q477690","display_name":"CUDA","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.33219999074935913},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.32690000534057617},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.32339999079704285},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3093000054359436},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3000999987125397},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.2777000069618225},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26829999685287476},{"id":"https://openalex.org/C50630238","wikidata":"https://www.wikidata.org/wiki/Q971505","display_name":"General-purpose computing on graphics processing units","level":3,"score":0.26350000500679016},{"id":"https://openalex.org/C192126672","wikidata":"https://www.wikidata.org/wiki/Q1068715","display_name":"Telecommunications network","level":2,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.15768","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15768","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.2604.15768","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15768","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"AI-driven":[0],"methods":[1],"have":[2],"demonstrated":[3],"considerable":[4],"success":[5],"in":[6,223],"tackling":[7],"the":[8,14,28,131,163,180,202,208],"central":[9],"challenge":[10],"of":[11,182],"accurately":[12],"solving":[13],"Schr\u00f6dinger":[15],"equation":[16],"for":[17,41,123],"complex":[18],"many-body":[19],"systems.":[20],"Among":[21],"neural":[22],"network":[23],"quantum":[24],"state":[25],"(NNQS)":[26],"approaches,":[27],"NNQS-SCI":[29,204],"(Selected":[30],"Configuration":[31],"Interaction)":[32],"method":[33],"stands":[34],"out":[35],"as":[36],"a":[37,57,67,86,99,142],"state-of-the-art":[38],"technique,":[39],"recognized":[40],"its":[42,48],"high":[43],"accuracy":[44],"and":[45,108,151,161],"scalability.":[46],"However,":[47],"application":[49],"to":[50,72,92,105,129,169,197],"larger":[51,158],"systems":[52],"is":[53],"severely":[54],"constrained":[55],"by":[56,136],"hybrid":[58],"CPU-GPU":[59],"architecture.":[60],"Specifically,":[61],"centralized":[62],"CPU-based":[63],"global":[64,102],"de-duplication":[65,103],"creates":[66],"severe":[68],"scalability":[69],"barrier":[70,134],"due":[71],"communication":[73,109],"bottlenecks,":[74],"while":[75,206],"host-resident":[76],"coupled-configuration":[77],"generation":[78],"induces":[79],"prohibitive":[80],"computational":[81],"overheads.":[82],"We":[83],"introduce":[84],"QiankunNet-cuSCI,":[85],"fully":[87],"GPU-accelerated":[88],"SCI":[89],"framework":[90],"designed":[91],"overcome":[93],"these":[94],"bottlenecks.":[95],"It":[96],"first":[97],"integrates":[98],"distributed,":[100],"load-balanced":[101],"algorithm":[104],"minimize":[106],"redundancy":[107],"overhead":[110],"at":[111],"scale.":[112],"To":[113],"address":[114],"compute":[115],"limitations,":[116],"it":[117,140,213],"employs":[118],"specialized,":[119],"fine-grained":[120],"CUDA":[121],"kernels":[122],"exact":[124],"coupled":[125],"configuration":[126,159],"generation.":[127],"Finally,":[128],"break":[130],"single-GPU":[132],"memory":[133],"exposed":[135],"this":[137],"full":[138],"acceleration,":[139],"incorporates":[141],"GPU":[143],"memory-centric":[144],"runtime":[145],"featuring":[146],"GPU-side":[147],"pooling,":[148],"streaming":[149],"mini-batches,":[150],"overlapped":[152],"offloading.":[153],"This":[154],"design":[155],"enables":[156],"much":[157],"spaces":[160],"shifts":[162],"bottleneck":[164],"from":[165],"host-side":[166],"limitations":[167],"back":[168],"on-device":[170],"inference.":[171],"Our":[172],"evaluation":[173],"demonstrates":[174,214],"that":[175],"our":[176,193],"work":[177,194],"fundamentally":[178],"expands":[179],"scale":[181],"solvable":[183],"problems.":[184],"On":[185],"an":[186],"NVIDIA":[187],"A100":[188],"cluster":[189],"with":[190],"64":[191],"GPUs,":[192],"achieves":[195],"up":[196],"2.32X":[198],"end-to-end":[199],"speedup":[200],"over":[201,219],"highly-optimized":[203],"baseline":[205],"preserving":[207],"same":[209],"chemical":[210],"accuracy.":[211],"Furthermore,":[212],"excellent":[215],"distributed":[216],"performance,":[217],"maintaining":[218],"90%":[220],"parallel":[221],"efficiency":[222],"strong":[224],"scaling":[225],"tests.":[226]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-21T00:00:00"}
