{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,25]],"date-time":"2026-10-25T23:21:05Z","timestamp":1792970465423,"version":"4.5.0"},"publisher-location":"New York, NY, USA","reference-count":34,"publisher":"ACM","license":[{"start":{"date-parts":[[2018,8,13]],"date-time":"2018-08-13T00:00:00Z","timestamp":1534118400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2018,8,13]]},"DOI":"10.1145\/3225058.3225069","type":"proceedings-article","created":{"date-parts":[[2018,8,8]],"date-time":"2018-08-08T19:13:06Z","timestamp":1533755586000},"page":"1-10","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":271,"title":["ImageNet Training in Minutes"],"prefix":"10.1145","author":[{"given":"Yang","family":"You","sequence":"first","affiliation":[{"name":"UC Berkeley"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"TACC"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cho-Jui","family":"Hsieh","sequence":"additional","affiliation":[{"name":"UC Davis"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James","family":"Demmel","sequence":"additional","affiliation":[{"name":"UC Berkeley"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kurt","family":"Keutzer","sequence":"additional","affiliation":[{"name":"UC Berkeley"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2018,8,13]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Extremely Large Minibatch SGD: Training ResNet-50 on ImageNet in 15 Minutes. arXiv preprint arXiv:1711.04325","author":"Akiba Takuya","year":"2017","unstructured":"Takuya Akiba , Shuji Suzuki , and Keisuke Fukuda . 2017. Extremely Large Minibatch SGD: Training ResNet-50 on ImageNet in 15 Minutes. arXiv preprint arXiv:1711.04325 ( 2017 ). Takuya Akiba, Shuji Suzuki, and Keisuke Fukuda. 2017. Extremely Large Minibatch SGD: Training ResNet-50 on ImageNet in 15 Minutes. arXiv preprint arXiv:1711.04325 (2017)."},{"key":"e_1_3_2_1_2_1","unstructured":"Dario Amodei Rishita Anubhai Eric Battenberg Carl Case Jared Casper Bryan Catanzaro Jingdong Chen Mike Chrzanowski Adam Coates Greg Diamos etal 2015. Deep speech 2: End-to-end speech recognition in english and mandarin. arXiv preprint arXiv:1512.02595 (2015).  Dario Amodei Rishita Anubhai Eric Battenberg Carl Case Jared Casper Bryan Catanzaro Jingdong Chen Mike Chrzanowski Adam Coates Greg Diamos et al. 2015. Deep speech 2: End-to-end speech recognition in english and mandarin. arXiv preprint arXiv:1512.02595 (2015)."},{"key":"e_1_3_2_1_3_1","volume-title":"https:\/\/www.technologyreview.com\/s\/602600\/deep-driving\/","author":"Reiley Carol","year":"2016","unstructured":"Carol Reiley . 2016. Deep Driving . ( 2016 ). https:\/\/www.technologyreview.com\/s\/602600\/deep-driving\/ . Carol Reiley. 2016. Deep Driving. (2016). https:\/\/www.technologyreview.com\/s\/602600\/deep-driving\/."},{"key":"e_1_3_2_1_4_1","unstructured":"Bryan Catanzaro. 2013. Deep learning with COTS HPC systems. (2013).  Bryan Catanzaro. 2013. Deep learning with COTS HPC systems. (2013)."},{"key":"e_1_3_2_1_5_1","volume-title":"Revisiting distributed synchronous SGD. arXiv preprint arXiv:1604.00981","author":"Chen Jianmin","year":"2016","unstructured":"Jianmin Chen , Rajat Monga , Samy Bengio , and Rafal Jozefowicz . 2016. Revisiting distributed synchronous SGD. arXiv preprint arXiv:1604.00981 ( 2016 ). Jianmin Chen, Rajat Monga, Samy Bengio, and Rafal Jozefowicz. 2016. Revisiting distributed synchronous SGD. arXiv preprint arXiv:1604.00981 (2016)."},{"key":"e_1_3_2_1_6_1","volume-title":"Distributed deep learning using synchronous stochastic gradient descent. arXiv preprint arXiv:1602.06709","author":"Das Dipankar","year":"2016","unstructured":"Dipankar Das , Sasikanth Avancha , Dheevatsa Mudigere , Karthikeyan Vaidynathan , Srinivas Sridharan , Dhiraj Kalamkar , Bharat Kaul , and Pradeep Dubey . 2016. Distributed deep learning using synchronous stochastic gradient descent. arXiv preprint arXiv:1602.06709 ( 2016 ). Dipankar Das, Sasikanth Avancha, Dheevatsa Mudigere, Karthikeyan Vaidynathan, Srinivas Sridharan, Dhiraj Kalamkar, Bharat Kaul, and Pradeep Dubey. 2016. Distributed deep learning using synchronous stochastic gradient descent. arXiv preprint arXiv:1602.06709 (2016)."},{"key":"e_1_3_2_1_7_1","unstructured":"Jeffrey Dean Greg Corrado Rajat Monga Kai Chen Matthieu Devin Mark Mao Andrew Senior Paul Tucker Ke Yang Quoc V Le etal 2012. Large scale distributed deep networks. In Advances in neural information processing systems. 1223--1231.   Jeffrey Dean Greg Corrado Rajat Monga Kai Chen Matthieu Devin Mark Mao Andrew Senior Paul Tucker Ke Yang Quoc V Le et al. 2012. Large scale distributed deep networks. In Advances in neural information processing systems. 1223--1231."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"e_1_3_2_1_9_1","unstructured":"Jack Dongarra Martin Meuer Horst Simon and Erich Strohmaier. 2017. Top500 supercomputer ranking. (2017). https:\/\/www.top500.org\/lists\/2017\/06\/  Jack Dongarra Martin Meuer Horst Simon and Erich Strohmaier. 2017. Top500 supercomputer ranking. (2017). https:\/\/www.top500.org\/lists\/2017\/06\/"},{"key":"e_1_3_2_1_10_1","volume-title":"Large Minibatch SGD: Training ImageNet in 1 Hour. arXiv preprint arXiv:1706.02677","author":"Goyal Priya","year":"2017","unstructured":"Priya Goyal , Piotr Doll\u00e1r , Ross Girshick , Pieter Noordhuis , Lukasz Wesolowski , Aapo Kyrola , Andrew Tulloch , Yangqing Jia , and Kaiming He. 2017. Accurate , Large Minibatch SGD: Training ImageNet in 1 Hour. arXiv preprint arXiv:1706.02677 ( 2017 ). Priya Goyal, Piotr Doll\u00e1r, Ross Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, and Kaiming He. 2017. Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour. arXiv preprint arXiv:1706.02677 (2017)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2553401"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/0167-8191(96)00024-5"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_14_1","volume-title":"Deep learning in finance. arXiv preprint arXiv:1602.06561","author":"Heaton JB","year":"2016","unstructured":"JB Heaton , NG Polson , and JH Witte . 2016. Deep learning in finance. arXiv preprint arXiv:1602.06561 ( 2016 ). JB Heaton, NG Polson, and JH Witte. 2016. Deep learning in finance. arXiv preprint arXiv:1602.06561 (2016)."},{"key":"e_1_3_2_1_15_1","volume-title":"Sequence Mining and Pattern Analysis in Drilling Reports with Deep Natural Language Processing. arXiv preprint arXiv:1712.01476","author":"Hoffimann J\u00falio","year":"2017","unstructured":"J\u00falio Hoffimann , Youli Mao , Avinash Wesley , and Aimee Taylor . 2017. Sequence Mining and Pattern Analysis in Drilling Reports with Deep Natural Language Processing. arXiv preprint arXiv:1712.01476 ( 2017 ). J\u00falio Hoffimann, Youli Mao, Avinash Wesley, and Aimee Taylor. 2017. Sequence Mining and Pattern Analysis in Drilling Reports with Deep Natural Language Processing. arXiv preprint arXiv:1712.01476 (2017)."},{"key":"e_1_3_2_1_16_1","volume-title":"FireCaffe: near-linear acceleration of deep neural network training on compute clusters. CoRR abs\/1511.00175","author":"Iandola Forrest N.","year":"2015","unstructured":"Forrest N. Iandola , Khalid Ashraf , Matthew W. Moskewicz , and Kurt Keutzer . 2015. FireCaffe: near-linear acceleration of deep neural network training on compute clusters. CoRR abs\/1511.00175 ( 2015 ). http:\/\/arxiv.org\/abs\/1511.00175 Forrest N. Iandola, Khalid Ashraf, Matthew W. Moskewicz, and Kurt Keutzer. 2015. FireCaffe: near-linear acceleration of deep neural network training on compute clusters. CoRR abs\/1511.00175 (2015). http:\/\/arxiv.org\/abs\/1511.00175"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.284"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2654889"},{"key":"e_1_3_2_1_19_1","volume-title":"How to scale distributed deep learning? arXiv preprint arXiv:1611.04581","author":"Jin Peter H","year":"2016","unstructured":"Peter H Jin , Qiaochu Yuan , Forrest Iandola , and Kurt Keutzer . 2016. How to scale distributed deep learning? arXiv preprint arXiv:1611.04581 ( 2016 ). Peter H Jin, Qiaochu Yuan, Forrest Iandola, and Kurt Keutzer. 2016. How to scale distributed deep learning? arXiv preprint arXiv:1611.04581 (2016)."},{"key":"e_1_3_2_1_20_1","volume-title":"On large-batch training for deep learning: Generalization gap and sharp minima. arXiv preprint arXiv:1609.04836","author":"Keskar Nitish Shirish","year":"2016","unstructured":"Nitish Shirish Keskar , Dheevatsa Mudigere , Jorge Nocedal , Mikhail Smelyanskiy , and Ping Tak Peter Tang . 2016. On large-batch training for deep learning: Generalization gap and sharp minima. arXiv preprint arXiv:1609.04836 ( 2016 ). Nitish Shirish Keskar, Dheevatsa Mudigere, Jorge Nocedal, Mikhail Smelyanskiy, and Ping Tak Peter Tang. 2016. On large-batch training for deep learning: Generalization gap and sharp minima. arXiv preprint arXiv:1609.04836 (2016)."},{"key":"e_1_3_2_1_21_1","volume-title":"One weird trick for parallelizing convolutional neural networks. arXiv preprint arXiv:1404.5997","author":"Krizhevsky Alex","year":"2014","unstructured":"Alex Krizhevsky . 2014. One weird trick for parallelizing convolutional neural networks. arXiv preprint arXiv:1404.5997 ( 2014 ). Alex Krizhevsky. 2014. One weird trick for parallelizing convolutional neural networks. arXiv preprint arXiv:1404.5997 (2014)."},{"key":"e_1_3_2_1_22_1","volume-title":"Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on. IEEE, 8595--8598","author":"Le Quoc V","year":"2013","unstructured":"Quoc V Le . 2013 . Building high-level features using large scale unsupervised learning. In Acoustics , Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on. IEEE, 8595--8598 . Quoc V Le. 2013. Building high-level features using large scale unsupervised learning. In Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on. IEEE, 8595--8598."},{"key":"e_1_3_2_1_24_1","volume-title":"2016 54th Annual Allerton Conference on. IEEE, 997--1004","author":"Mitliagkas Ioannis","year":"2016","unstructured":"Ioannis Mitliagkas , Ce Zhang , Stefan Hadjis , and Christopher R\u00e9 . 2016 . Asynchrony begets momentum, with an application to deep learning. In Communication, Control, and Computing (Allerton) , 2016 54th Annual Allerton Conference on. IEEE, 997--1004 . Ioannis Mitliagkas, Ce Zhang, Stefan Hadjis, and Christopher R\u00e9. 2016. Asynchrony begets momentum, with an application to deep learning. In Communication, Control, and Computing (Allerton), 2016 54th Annual Allerton Conference on. IEEE, 997--1004."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-24685-5_1"},{"key":"e_1_3_2_1_26_1","volume-title":"More efficient reduction algorithms for non-power-of-two number of processors in message-passing parallel systems","author":"Rabenseifner Rolf","unstructured":"Rolf Rabenseifner and Jesper Larsson Tr\u00e4ff . 2004. More efficient reduction algorithms for non-power-of-two number of processors in message-passing parallel systems . In PVM\/MPI. Springer , 36--46. Rolf Rabenseifner and Jesper Larsson Tr\u00e4ff. 2004. More efficient reduction algorithms for non-power-of-two number of processors in message-passing parallel systems. In PVM\/MPI. Springer, 36--46."},{"key":"e_1_3_2_1_27_1","volume-title":"Hogwild: A lock-free approach to parallelizing stochastic gradient descent. In Advances in Neural Information Processing Systems. 693--701.","author":"Recht Benjamin","year":"2011","unstructured":"Benjamin Recht , Christopher Re , Stephen Wright , and Feng Niu . 2011 . Hogwild: A lock-free approach to parallelizing stochastic gradient descent. In Advances in Neural Information Processing Systems. 693--701. Benjamin Recht, Christopher Re, Stephen Wright, and Feng Niu. 2011. Hogwild: A lock-free approach to parallelizing stochastic gradient descent. In Advances in Neural Information Processing Systems. 693--701."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"crossref","unstructured":"Frank Seide Hao Fu Jasha Droppo Gang Li and Dong Yu. 2014. 1-bit stochastic gradient descent and its application to data-parallel distributed training of speech DNNs.. In Interspeech. 1058--1062.  Frank Seide Hao Fu Jasha Droppo Gang Li and Dong Yu. 2014. 1-bit stochastic gradient descent and its application to data-parallel distributed training of speech DNNs.. In Interspeech. 1058--1062.","DOI":"10.21437\/Interspeech.2014-274"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2014.6853593"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1177\/1094342005051521"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1006\/jpdc.1994.1091"},{"key":"e_1_3_2_1_32_1","unstructured":"Yang You Igor Gitman and Boris Ginsburg. 2017. Scaling SGD Batch Size to 32K for ImageNet Training. (2017).  Yang You Igor Gitman and Boris Ginsburg. 2017. Scaling SGD Batch Size to 32K for ImageNet Training. (2017)."},{"key":"e_1_3_2_1_33_1","volume-title":"ImageNet Training in 24 Minutes. arXiv preprint arXiv:1709.05011","author":"You Yang","year":"2017","unstructured":"Yang You , Zhao Zhang , James Demmel , Kurt Keutzer , and Cho-Jui Hsieh . 2017. ImageNet Training in 24 Minutes. arXiv preprint arXiv:1709.05011 ( 2017 ). Yang You, Zhao Zhang, James Demmel, Kurt Keutzer, and Cho-Jui Hsieh. 2017. ImageNet Training in 24 Minutes. arXiv preprint arXiv:1709.05011 (2017)."},{"key":"e_1_3_2_1_34_1","unstructured":"Sixin Zhang Anna E Choromanska and Yann LeCun. 2015. Deep learning with elastic averaging SGD. In Advances in Neural Information Processing Systems. 685--693.   Sixin Zhang Anna E Choromanska and Yann LeCun. 2015. Deep learning with elastic averaging SGD. In Advances in Neural Information Processing Systems. 685--693."},{"key":"e_1_3_2_1_35_1","unstructured":"Sixin Zhang Anna E Choromanska and Yann LeCun. 2015. Deep learning with elastic averaging SGD. In Advances in Neural Information Processing Systems. 685--693.   Sixin Zhang Anna E Choromanska and Yann LeCun. 2015. Deep learning with elastic averaging SGD. In Advances in Neural Information Processing Systems. 685--693."}],"event":{"name":"ICPP 2018: 47th International Conference on Parallel Processing","location":"Eugene OR USA","acronym":"ICPP 2018","sponsor":["University of Oregon University of Oregon"]},"container-title":["Proceedings of the 47th International Conference on Parallel Processing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3225058.3225069","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3225058.3225069","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T01:39:06Z","timestamp":1750210746000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3225058.3225069"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,13]]},"references-count":34,"alternative-id":["10.1145\/3225058.3225069","10.1145\/3225058"],"URL":"https:\/\/doi.org\/10.1145\/3225058.3225069","relation":{},"subject":[],"published":{"date-parts":[[2018,8,13]]},"assertion":[{"value":"2018-08-13","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}