{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T18:05:35Z","timestamp":1730225135938,"version":"3.28.0"},"reference-count":36,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T00:00:00Z","timestamp":1669852800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T00:00:00Z","timestamp":1669852800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12]]},"DOI":"10.1109\/hipc56025.2022.00019","type":"proceedings-article","created":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T17:57:12Z","timestamp":1682531832000},"page":"48-58","source":"Crossref","is-referenced-by-count":1,"title":["Building a Performance Model for Deep Learning Recommendation Model Training on GPUs"],"prefix":"10.1109","author":[{"given":"Zhongyi","family":"Lin","sequence":"first","affiliation":[{"name":"University of California, Davis,Department of Elect. & Comp. Engr.,Davis,California"}]},{"given":"Louis","family":"Feng","sequence":"additional","affiliation":[{"name":"Meta Platforms, Inc.,Menlo Park,California"}]},{"given":"Ehsan K.","family":"Ardestani","sequence":"additional","affiliation":[{"name":"Meta Platforms, Inc.,Menlo Park,California"}]},{"given":"Jaewon","family":"Lee","sequence":"additional","affiliation":[{"name":"Meta Platforms, Inc.,Menlo Park,California"}]},{"given":"John","family":"Lundell","sequence":"additional","affiliation":[{"name":"Meta Platforms, Inc.,Menlo Park,California"}]},{"given":"Changkyu","family":"Kim","sequence":"additional","affiliation":[{"name":"Meta Platforms, Inc.,Menlo Park,California"}]},{"given":"Arun","family":"Kejariwal","sequence":"additional","affiliation":[{"name":"Meta Platforms, Inc.,Menlo Park,California"}]},{"given":"John D.","family":"Owens","sequence":"additional","affiliation":[{"name":"University of California, Davis,Department of Elect. & Comp. Engr.,Davis,California"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-7637-6_2"},{"journal-title":"DLRM Github repo","year":"2019","key":"ref35"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/358916.358995"},{"key":"ref34","first-page":"8026","article-title":"PyTorch: An imperative style, high-performance deep learning library","author":"paszke","year":"2019","journal-title":"Advances in Neural IInformation Processing Systems"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988454"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/239"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2017.04.002"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPS.2018.00067"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2015.2412549"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1093\/biomet\/54.1-2.167","article-title":"Estimation of the probability of an event as a function of several independent variables","volume":"54","author":"walker","year":"1967","journal-title":"Biometrika"},{"first-page":"265","article-title":"TensorFlow: A system for large-scale machine learning","year":"0","author":"abadi","key":"ref33"},{"journal-title":"CoRR","article-title":"Deep learning recommendation model for personalization and recommendation systems","year":"2019","author":"naumov","key":"ref10"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2654889"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/MIC.2017.72"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3340922"},{"article-title":"Deep & cross network for ad click predictions","year":"0","author":"wang","key":"ref17"},{"first-page":"1754","article-title":"XDeepFM: Combining explicit and implicit feature interactions for recommender systems","year":"0","author":"lian","key":"ref16"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/1498765.1498785"},{"first-page":"1059","article-title":"Deep interest network for click-through rate prediction","year":"0","author":"zhou","key":"ref18"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8622396"},{"key":"ref23","article-title":"Computational performance predictions for deep neural network training: A runtime-based approach","volume":"abs 2102 527","author":"yu","year":"2021","journal-title":"CoRR"},{"first-page":"337","article-title":"Daydream: Accurately estimating the efficacy of optimizations for DNN training","year":"0","author":"zhu","key":"ref26"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2916550"},{"year":"2020","key":"ref20","article-title":"cuBLAS deep learning performance matrix multiplication"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICS51289.2020.00039"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ISPASS.2019.00041"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS47774.2020.00097"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00112"},{"journal-title":"Batch embedding lookup GPU kernel and more","year":"2020","author":"tulloch","key":"ref29"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"article-title":"Distributed hierarchical GPU parameter server for massive scale deep learning ads systems","year":"0","author":"zhao","key":"ref7"},{"key":"ref9","article-title":"Attention is all you need","volume":"30","author":"vaswani","year":"2017","journal-title":"Advances in neural information processing systems"},{"first-page":"703","article-title":"Learning representations of hierarchical slates in collaborative filtering","year":"0","author":"elahi","key":"ref4"},{"first-page":"191","article-title":"Deep neural networks for YouTube recommendations","year":"0","author":"covington","key":"ref3"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3358045"},{"first-page":"945","article-title":"Towards automated neural interaction discovery for click-through rate prediction","year":"0","author":"song","key":"ref5"}],"event":{"name":"2022 IEEE 29th International Conference on High Performance Computing, Data, and Analytics (HiPC)","start":{"date-parts":[[2022,12,18]]},"location":"Bengaluru, India","end":{"date-parts":[[2022,12,21]]}},"container-title":["2022 IEEE 29th International Conference on High Performance Computing, Data, and Analytics (HiPC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10106277\/10106278\/10106317.pdf?arnumber=10106317","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,15]],"date-time":"2023-05-15T17:46:51Z","timestamp":1684172811000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10106317\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12]]},"references-count":36,"URL":"http:\/\/dx.doi.org\/10.1109\/hipc56025.2022.00019","relation":{},"subject":[],"published":{"date-parts":[[2022,12]]}}}