{"id":"https://openalex.org/W4401408762","doi":"https://doi.org/10.1145/3673038.3673107","title":"Dissecting Convolutional Neural Networks for Runtime and Scalability Prediction","display_name":"Dissecting Convolutional Neural Networks for Runtime and Scalability Prediction","publication_year":2024,"publication_date":"2024-08-08","ids":{"openalex":"https://openalex.org/W4401408762","doi":"https://doi.org/10.1145/3673038.3673107"},"language":"en","primary_location":{"id":"doi:10.1145/3673038.3673107","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3673038.3673107","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 53rd International Conference on Parallel Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3673038.3673107","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5106355546","display_name":"Tim Beringer","orcid":"https://orcid.org/0000-0002-1783-172X"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technische Universit\u00e4t Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tim Beringer","raw_affiliation_strings":["Technical University of Darmstadt, Germany"],"raw_orcid":"https://orcid.org/0000-0002-1783-172X","affiliations":[{"raw_affiliation_string":"Technical University of Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091128607","display_name":"J. Stock","orcid":"https://orcid.org/0009-0009-3374-4472"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technische Universit\u00e4t Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jakob Stock","raw_affiliation_strings":["Technical University of Darmstadt, Germany"],"raw_orcid":"https://orcid.org/0009-0009-3374-4472","affiliations":[{"raw_affiliation_string":"Technical University of Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028887858","display_name":"Arya Mazaheri","orcid":"https://orcid.org/0000-0002-5671-4710"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technische Universit\u00e4t Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Arya Mazaheri","raw_affiliation_strings":["Technical University of Darmstadt, Germany"],"raw_orcid":"https://orcid.org/0000-0002-5671-4710","affiliations":[{"raw_affiliation_string":"Technical University of Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018089961","display_name":"Felix Wolf","orcid":"https://orcid.org/0000-0001-6595-3599"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technische Universit\u00e4t Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Felix Wolf","raw_affiliation_strings":["Technical University of Darmstadt, Germany"],"raw_orcid":"https://orcid.org/0000-0001-6595-3599","affiliations":[{"raw_affiliation_string":"Technical University of Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I31512782"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10923535,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"168","last_page":"178"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9735000133514404,"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"}},"topics":[{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9735000133514404,"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"}},{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9696999788284302,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.967199981212616,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.827712893486023},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7837961912155151},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7362391352653503},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4301531910896301},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.34588098526000977},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.3423812985420227},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32020485401153564},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.12226760387420654}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.827712893486023},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7837961912155151},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7362391352653503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4301531910896301},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.34588098526000977},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3423812985420227},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32020485401153564},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.12226760387420654}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3673038.3673107","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3673038.3673107","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 53rd International Conference on Parallel Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3673038.3673107","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3673038.3673107","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 53rd International Conference on Parallel Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2885311373","https://openalex.org/W2946408574","https://openalex.org/W2981563141","https://openalex.org/W3034429256","https://openalex.org/W3121689374","https://openalex.org/W3135013702","https://openalex.org/W3152795099","https://openalex.org/W3165698711","https://openalex.org/W3168716227","https://openalex.org/W4221113823","https://openalex.org/W6603394118","https://openalex.org/W6603957568","https://openalex.org/W6604186633","https://openalex.org/W6604344240","https://openalex.org/W6607459698","https://openalex.org/W6629448196","https://openalex.org/W6753278433","https://openalex.org/W6819060087"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W4293226380","https://openalex.org/W4235240664","https://openalex.org/W1982914007","https://openalex.org/W2159583675","https://openalex.org/W1824242903","https://openalex.org/W1493858311","https://openalex.org/W2155470929","https://openalex.org/W2394465510","https://openalex.org/W2111125783"],"abstract_inverted_index":{"Given":[0],"the":[1,35,68,110,117,152],"computational":[2],"complexity":[3],"of":[4,11,71,102,112,134,144,154],"deep":[5],"neural":[6,97],"networks":[7,98],"(DNN),":[8],"accurate":[9],"prediction":[10,111],"their":[12,83],"training":[13,115,137],"and":[14,26,38,43,50,77,85,114,136,148,158],"inference":[15,36,113,135],"time":[16,37,48],"using":[17],"performance":[18,64,88],"modeling":[19],"is":[20],"crucial":[21],"for":[22,106],"efficient":[23],"infrastructure":[24],"planning":[25],"DNN":[27],"development.":[28],"However,":[29],"existing":[30],"methods":[31],"often":[32],"predict":[33],"only":[34],"rely":[39],"on":[40,95,119],"exhaustive":[41],"benchmarking":[42],"fine":[44],"tuning,":[45],"making":[46,151],"them":[47],"consuming":[49],"restricted":[51],"in":[52],"scope.":[53],"As":[54],"a":[55,60,100],"remedy,":[56],"we":[57],"propose":[58],"ConvMeter,":[59],"novel":[61],"yet":[62],"simple":[63],"model":[65],"that":[66,130],"considers":[67],"inherent":[69],"characteristics":[70],"DNNs,":[72],"such":[73],"as":[74],"architecture,":[75],"dataset,":[76],"target":[78],"hardware,":[79],"which":[80,90],"strongly":[81],"affect":[82],"runtime":[84,132],"scalability.":[86],"Our":[87],"model,":[89],"has":[91],"been":[92],"thoroughly":[93],"tested":[94],"convolutional":[96],"(ConvNets),":[99],"class":[101],"DNNs":[103],"widely":[104],"used":[105],"image":[107],"analysis,":[108],"offers":[109],"time,":[116],"latter":[118],"one":[120],"or":[121],"more":[122],"compute":[123],"nodes.":[124],"Experiments":[125],"with":[126],"various":[127],"ConvNets":[128,155],"demonstrate":[129],"our":[131],"predictions":[133],"phases":[138],"achieved":[139],"an":[140],"average":[141],"error":[142],"rate":[143],"less":[145],"than":[146],"20%":[147],"18%,":[149],"respectively,":[150],"assessment":[153],"regarding":[156],"efficiency":[157],"scalability":[159],"straightforward.":[160]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
