{"id":"https://openalex.org/W4387323625","doi":"https://doi.org/10.48550/arxiv.2310.00496","title":"The Sparsity Roofline: Understanding the Hardware Limits of Sparse Neural Networks","display_name":"The Sparsity Roofline: Understanding the Hardware Limits of Sparse Neural Networks","publication_year":2023,"publication_date":"2023-09-30","ids":{"openalex":"https://openalex.org/W4387323625","doi":"https://doi.org/10.48550/arxiv.2310.00496"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2310.00496","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.00496","pdf_url":"https://arxiv.org/pdf/2310.00496","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":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2310.00496","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092998391","display_name":"Cameron Shinn","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shinn, Cameron","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043458446","display_name":"Collin McCarthy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"McCarthy, Collin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033185286","display_name":"Saurav Muralidharan","orcid":"https://orcid.org/0000-0003-4024-3958"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Muralidharan, Saurav","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014326676","display_name":"Muhammad Osama","orcid":"https://orcid.org/0000-0002-5023-5348"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Osama, Muhammad","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5028662746","display_name":"John D. Owens","orcid":"https://orcid.org/0000-0001-6582-8237"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Owens, John D.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5092998391"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9940000176429749,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9940000176429749,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9902999997138977,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9868000149726868,"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":0.9611015319824219},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7953004837036133},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6147251725196838},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6095711588859558},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.5387173295021057},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4662190079689026},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4390827715396881},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4123852550983429},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37047046422958374},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3511694073677063},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.2849116325378418},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1052527129650116}],"concepts":[{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.9611015319824219},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7953004837036133},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6147251725196838},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6095711588859558},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.5387173295021057},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4662190079689026},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4390827715396881},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4123852550983429},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37047046422958374},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3511694073677063},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.2849116325378418},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1052527129650116},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2310.00496","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.00496","pdf_url":"https://arxiv.org/pdf/2310.00496","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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2310.00496","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2310.00496","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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2310.00496","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.00496","pdf_url":"https://arxiv.org/pdf/2310.00496","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":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.44999998807907104,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4387323625.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2000169967","https://openalex.org/W2097707447"],"abstract_inverted_index":{"We":[0,56,89],"introduce":[1],"the":[2,38,44,48,71,91,111,129,145,155],"Sparsity":[3,16,146],"Roofline,":[4],"a":[5,60,82],"visual":[6],"performance":[7,112,130,149,157],"model":[8,63,97],"for":[9,64],"evaluating":[10],"sparsity":[11,85,118,134,152],"in":[12,140],"neural":[13],"networks.":[14],"The":[15],"Roofline":[17,147],"jointly":[18],"models":[19],"network":[20,67],"accuracy,":[21],"sparsity,":[22],"and":[23,33,37,51,69,87,93,120,136],"theoretical":[24,39],"inference":[25],"speedup.":[26],"Our":[27],"approach":[28],"does":[29],"not":[30],"require":[31],"implementing":[32],"benchmarking":[34],"optimized":[35],"kernels,":[36],"speedup":[40,46,73],"becomes":[41],"equal":[42],"to":[43],"actual":[45],"when":[47],"corresponding":[49],"dense":[50],"sparse":[52,66,137],"kernels":[53],"are":[54],"well-optimized.":[55],"achieve":[57],"this":[58],"through":[59,98],"novel":[61],"analytical":[62],"predicting":[65],"performance,":[68],"validate":[70],"predicted":[72],"using":[74],"several":[75],"real-world":[76],"computer":[77],"vision":[78],"architectures":[79],"pruned":[80],"across":[81],"range":[83],"of":[84,95,113,132],"patterns":[86,135],"degrees.":[88],"demonstrate":[90],"utility":[92],"ease-of-use":[94],"our":[96],"two":[99],"case":[100],"studies:":[101],"(1)":[102],"we":[103,122],"show":[104,123],"how":[105,124],"machine":[106],"learning":[107],"researchers":[108],"can":[109,127],"predict":[110,128],"unimplemented":[114],"or":[115],"unoptimized":[116],"block-structured":[117],"patterns,":[119],"(2)":[121],"hardware":[125],"designers":[126],"implications":[131],"new":[133],"data":[138],"formats":[139],"hardware.":[141],"In":[142],"both":[143],"scenarios,":[144],"helps":[148],"experts":[150],"identify":[151],"regimes":[153],"with":[154],"highest":[156],"potential.":[158]},"counts_by_year":[],"updated_date":"2026-03-14T08:43:22.919905","created_date":"2023-10-04T00:00:00"}
