{"id":"https://openalex.org/W4406462012","doi":"https://doi.org/10.1109/bigdata62323.2024.10825791","title":"A Study of Data-Path Bugs in PyTorch with a Focus on Memory Issues","display_name":"A Study of Data-Path Bugs in PyTorch with a Focus on Memory Issues","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406462012","doi":"https://doi.org/10.1109/bigdata62323.2024.10825791"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825791","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825791","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://scholarsphere.psu.edu/resources/1ce3f489-93e6-4197-8153-91d190e83b37/downloads/46567","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115905224","display_name":"Rubayet Rahman Rongon","orcid":null},"institutions":[{"id":"https://openalex.org/I137317281","display_name":"Washington State University Vancouver","ror":"https://ror.org/00g2fk805","country_code":"US","type":"education","lineage":["https://openalex.org/I137317281","https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rubayet Rahman Rongon","raw_affiliation_strings":["Washington State University,Vancouver,Washington"],"affiliations":[{"raw_affiliation_string":"Washington State University,Vancouver,Washington","institution_ids":["https://openalex.org/I137317281"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102836248","display_name":"Chen Cao","orcid":"https://orcid.org/0009-0001-2600-2819"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen Cao","raw_affiliation_strings":["Pennsylvania State University Behrend,Erie,Pennsylvania"],"affiliations":[{"raw_affiliation_string":"Pennsylvania State University Behrend,Erie,Pennsylvania","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101979632","display_name":"Xuechen Zhang","orcid":"https://orcid.org/0000-0002-0907-0027"},"institutions":[{"id":"https://openalex.org/I137317281","display_name":"Washington State University Vancouver","ror":"https://ror.org/00g2fk805","country_code":"US","type":"education","lineage":["https://openalex.org/I137317281","https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuechen Zhang","raw_affiliation_strings":["Washington State University,Vancouver,Washington"],"affiliations":[{"raw_affiliation_string":"Washington State University,Vancouver,Washington","institution_ids":["https://openalex.org/I137317281"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5115905224"],"corresponding_institution_ids":["https://openalex.org/I137317281"],"apc_list":null,"apc_paid":null,"fwci":0.3638,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61672216,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"292","last_page":"301"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9919999837875366,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7654101848602295},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.7082427144050598},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.6292743682861328},{"id":"https://openalex.org/keywords/software-bug","display_name":"Software bug","score":0.5332443714141846},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.39091265201568604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.352929949760437},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3391185402870178},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.25614872574806213},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.1786939799785614}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7654101848602295},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.7082427144050598},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.6292743682861328},{"id":"https://openalex.org/C1009929","wikidata":"https://www.wikidata.org/wiki/Q179550","display_name":"Software bug","level":3,"score":0.5332443714141846},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.39091265201568604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.352929949760437},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3391185402870178},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.25614872574806213},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.1786939799785614},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825791","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825791","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},{"id":"pmh:oai:scholarsphere.psu.edu:95d2c94a-0bff-4324-8d2a-369277c34e4c","is_oa":true,"landing_page_url":"https://scholarsphere.psu.edu/resources/95d2c94a-0bff-4324-8d2a-369277c34e4c","pdf_url":"https://scholarsphere.psu.edu/resources/1ce3f489-93e6-4197-8153-91d190e83b37/downloads/46567","source":{"id":"https://openalex.org/S4306401507","display_name":"ScholarSphere (Penn State Libraries)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I3130638595","host_organization_name":"Pangasinan State University","host_organization_lineage":["https://openalex.org/I3130638595"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:scholarsphere.psu.edu:95d2c94a-0bff-4324-8d2a-369277c34e4c","is_oa":true,"landing_page_url":"https://scholarsphere.psu.edu/resources/95d2c94a-0bff-4324-8d2a-369277c34e4c","pdf_url":"https://scholarsphere.psu.edu/resources/1ce3f489-93e6-4197-8153-91d190e83b37/downloads/46567","source":{"id":"https://openalex.org/S4306401507","display_name":"ScholarSphere (Penn State Libraries)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I3130638595","host_organization_name":"Pangasinan State University","host_organization_lineage":["https://openalex.org/I3130638595"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4406462012.pdf"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W2049875313","https://openalex.org/W2126665310","https://openalex.org/W2138011018","https://openalex.org/W2187303492","https://openalex.org/W2344706860","https://openalex.org/W2588061952","https://openalex.org/W2988675576","https://openalex.org/W3096835151","https://openalex.org/W3118608800","https://openalex.org/W3123045479","https://openalex.org/W3198396679","https://openalex.org/W4213072374","https://openalex.org/W4238383446","https://openalex.org/W4252681483","https://openalex.org/W4312647711","https://openalex.org/W4312757284","https://openalex.org/W4316116762","https://openalex.org/W4319594569","https://openalex.org/W4327594616","https://openalex.org/W4389141459","https://openalex.org/W4389337865","https://openalex.org/W4389544184","https://openalex.org/W4394998892","https://openalex.org/W6679025200","https://openalex.org/W6793480809","https://openalex.org/W6839584638"],"related_works":["https://openalex.org/W2012531322","https://openalex.org/W2402761219","https://openalex.org/W2785900585","https://openalex.org/W2353730437","https://openalex.org/W2490303674","https://openalex.org/W2609066826","https://openalex.org/W2810752900","https://openalex.org/W2365677836","https://openalex.org/W2531295127","https://openalex.org/W3186538219"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,17],"comprehensive":[4],"and":[5,47,54,92,103,143,179,190,199,206],"quantitative":[6],"study":[7],"of":[8,86,90,108,133,181],"bugs":[9,25,63,68,82,91,115,202],"related":[10,69],"to":[11,30,70,100,112,121,163,197],"Data":[12],"Path":[13],"in":[14,22,72,74,124,203],"PyTorch":[15,73],"with":[16,193],"focus":[18],"on":[19,176],"tensor":[20,55,141,145,152,171,207],"management":[21],"memory.":[23],"The":[24],"were":[26],"reported":[27],"from":[28,118],"2017":[29],"2024.":[31],"Analyzing":[32],"3,089":[33],"closed":[34],"issues,":[35],"we":[36,137],"identified":[37],"11":[38],"distinct":[39],"bug":[40],"types":[41],"affecting":[42],"the":[43,78,87,95,109,131,155,166,177],"data":[44,120,123,204],"storage,":[45],"allocation,":[46],"loading,":[48],"including":[49],"memory":[50,79,125,134,208],"bugs,":[51,80],"indexing":[52],"errors,":[53],"contiguity":[56,153],"violations.":[57],"Our":[58,147,183],"analysis":[59],"reveals":[60],"that":[61,150],"data-path":[62],"have":[64,94],"more":[65],"occurrences":[66],"than":[67],"computation":[71],"recent":[75],"years.":[76],"Among":[77],"non-contiguity":[81,114],"account":[83],"for":[84,169,188],"30.2%":[85],"total":[88],"number":[89,178],"they":[93],"most":[96],"significant":[97],"impact,":[98],"leading":[99],"both":[101],"crashes":[102],"silent":[104],"correctness":[105],"failures.":[106],"One":[107],"common":[110],"solutions":[111],"addressing":[113],"is":[116],"transforming":[117],"non-contiguous":[119,144,170],"contiguous":[122],"before":[126],"machine-learning":[127],"computation.":[128],"To":[129],"assess":[130],"impact":[132],"layout":[135],"transformation,":[136],"conducted":[138],"experiments":[139],"involving":[140],"augmentation":[142,156],"conversion.":[146],"findings":[148],"demonstrate":[149],"maintaining":[151],"throughout":[154],"process":[157],"can":[158],"improve":[159],"performance":[160],"by":[161],"up":[162],"49.6%,":[164],"while":[165],"time":[167],"required":[168],"conversion":[172],"varies":[173],"significantly":[174],"based":[175],"order":[180],"dimensions.":[182],"research":[184],"provides":[185],"valuable":[186],"insights":[187],"developers":[189],"researchers":[191],"working":[192],"PyTorch,":[194],"helping":[195],"them":[196],"identify":[198],"address":[200],"potential":[201],"paths":[205],"management.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}