{"id":"https://openalex.org/W4366459056","doi":"https://doi.org/10.48550/arxiv.2304.08880","title":"NPS: A Framework for Accurate Program Sampling Using Graph Neural Network","display_name":"NPS: A Framework for Accurate Program Sampling Using Graph Neural Network","publication_year":2023,"publication_date":"2023-04-18","ids":{"openalex":"https://openalex.org/W4366459056","doi":"https://doi.org/10.48550/arxiv.2304.08880"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2304.08880","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2304.08880","pdf_url":"https://arxiv.org/pdf/2304.08880","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2304.08880","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102291852","display_name":"Yuanwei Fang","orcid":"https://orcid.org/0000-0001-5600-026X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang, Yuanwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100323075","display_name":"Zihao Liu","orcid":"https://orcid.org/0000-0003-0488-9348"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zihao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030346188","display_name":"Yanheng Lu","orcid":"https://orcid.org/0000-0001-8087-221X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Yanheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100320734","display_name":"Jiawei Liu","orcid":"https://orcid.org/0000-0001-7122-8625"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jiawei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100654832","display_name":"Jiajie Li","orcid":"https://orcid.org/0000-0002-4086-4765"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jiajie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014513107","display_name":"Yi Jin","orcid":"https://orcid.org/0000-0001-6203-1281"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100326440","display_name":"Jian Chen","orcid":"https://orcid.org/0000-0002-2097-5740"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052911398","display_name":"Yenkuang Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yenkuang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046896624","display_name":"Hongzhong Zheng","orcid":"https://orcid.org/0000-0001-7696-9799"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Hongzhong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100385336","display_name":"Yuan Xie","orcid":"https://orcid.org/0000-0003-2093-1788"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Yuan","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":true,"cited_by_count":1,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9932000041007996,"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":0.9932000041007996,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.9868000149726868,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9811000227928162,"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/computer-science","display_name":"Computer science","score":0.8516812324523926},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46821001172065735},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.42370879650115967},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.41420426964759827},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4101225733757019},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28805017471313477},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2425667643547058}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8516812324523926},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46821001172065735},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.42370879650115967},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.41420426964759827},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4101225733757019},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28805017471313477},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2425667643547058}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2304.08880","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2304.08880","pdf_url":"https://arxiv.org/pdf/2304.08880","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2304.08880","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2304.08880","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":"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":"pmh:oai:arXiv.org:2304.08880","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2304.08880","pdf_url":"https://arxiv.org/pdf/2304.08880","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.6299999952316284,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4366459056.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W2530322880"],"abstract_inverted_index":{"With":[0],"the":[1,49,151,161,175,188,197],"end":[2],"of":[3,94,199],"Moore's":[4],"Law,":[5],"there":[6],"is":[7,29,138],"a":[8,30,84,95,123,141],"growing":[9],"demand":[10],"for":[11,42,52,102],"rapid":[12],"architectural":[13],"innovations":[14],"in":[15,33,126,192],"modern":[16],"processors,":[17],"such":[18,128],"as":[19,36,115,129],"RISC-V":[20],"custom":[21],"extensions,":[22],"to":[23,158],"continue":[24],"performance":[25],"scaling.":[26],"Program":[27,81],"sampling":[28],"crucial":[31],"step":[32],"microprocessor":[34],"design,":[35],"it":[37],"selects":[38],"representative":[39],"simulation":[40],"points":[41],"workload":[43],"simulation.":[44],"While":[45],"SimPoint":[46,155],"has":[47],"been":[48],"de-facto":[50],"approach":[51,191],"decades,":[53],"its":[54],"limited":[55],"expressiveness":[56],"with":[57,140,171],"Basic":[58],"Block":[59],"Vector":[60],"(BBV)":[61],"requires":[62],"time-consuming":[63],"human":[64],"tuning,":[65],"often":[66],"taking":[67],"months,":[68],"which":[69],"impedes":[70],"fast":[71],"innovation":[72],"and":[73,110,119,134,185],"agile":[74],"hardware":[75],"development.":[76],"This":[77],"paper":[78],"introduces":[79],"Neural":[80,97],"Sampling":[82],"(NPS),":[83],"novel":[85],"framework":[86],"that":[87,145],"learns":[88],"execution":[89,201],"embeddings":[90],"using":[91],"dynamic":[92],"snapshots":[93],"Graph":[96],"Network.":[98],"NPS":[99,153,167,181],"deploys":[100],"AssemblyNet":[101,113,137],"embedding":[103],"generation,":[104],"leveraging":[105],"an":[106],"application's":[107],"code":[108,132,193],"structures":[109],"runtime":[111],"states.":[112],"serves":[114],"NPS's":[116],"graph":[117],"model":[118],"neural":[120],"architecture,":[121],"capturing":[122],"program's":[124],"behavior":[125,194],"aspects":[127],"data":[130,135,142],"computation,":[131],"path,":[133],"flow.":[136],"trained":[139],"prefetch":[143],"task":[144],"predicts":[146],"consecutive":[147],"memory":[148],"addresses.":[149],"In":[150],"experiments,":[152],"outperforms":[154],"by":[156,164],"up":[157],"63%,":[159],"reducing":[160,174],"average":[162],"error":[163],"38%.":[165],"Additionally,":[166],"demonstrates":[168],"strong":[169],"robustness":[170],"increased":[172],"accuracy,":[173],"expensive":[176],"accuracy":[177,184],"tuning":[178],"overhead.":[179],"Furthermore,":[180],"shows":[182],"higher":[183],"generality":[186],"than":[187],"state-of-the-art":[189],"GNN":[190],"learning,":[195],"enabling":[196],"generation":[198],"high-quality":[200],"embeddings.":[202]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}