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(2016).","DOI":"10.1109\/CVPR.2016.308"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_40_1","unstructured":"Reference ncf implementation using pytorch in mlperf. (https:\/\/github.com\/mlperf\/training\/blob\/master\/recommendation\/pytorch\/README.md).  Reference ncf implementation using pytorch in mlperf. (https:\/\/github.com\/mlperf\/training\/blob\/master\/recommendation\/pytorch\/README.md)."},{"issue":"4","key":"e_1_3_2_1_41_1","first-page":"19","volume":"5","author":"Harper F Maxwell","unstructured":"Harper , F Maxwell and Konstan , Joseph A. \"the movielens datasets: History and context\". ACM Trans. Interact. Intell. Syst. 5 ( 4 ): 19 . (2015). Harper, F Maxwell and Konstan, Joseph A. \"the movielens datasets: History and context\". ACM Trans. Interact. Intell. Syst. 5(4):19. (2015).","journal-title":"ACM Trans. Interact. Intell. Syst."},{"key":"e_1_3_2_1_42_1","unstructured":"Ncf implementation in bigdl. (https:\/\/github.com\/mlperf\/training_results_v0.5\/tree\/master\/v0.5.0\/intel\/intel_ncf_submission).  Ncf implementation in bigdl. (https:\/\/github.com\/mlperf\/training_results_v0.5\/tree\/master\/v0.5.0\/intel\/intel_ncf_submission)."},{"key":"e_1_3_2_1_43_1","unstructured":"Mlperf 0.5 training results. (https:\/\/mlperf.org\/training-results-0-5).  Mlperf 0.5 training results. (https:\/\/mlperf.org\/training-results-0-5)."},{"key":"e_1_3_2_1_44_1","unstructured":"Jason (Jinquan) Dai and Ding Ding. Very large-scale distributed deep learning with bigdl. o'reilly ai conference san francisco. (2017).  Jason (Jinquan) Dai and Ding Ding. Very large-scale distributed deep learning with bigdl. o'reilly ai conference san francisco. (2017)."},{"key":"e_1_3_2_1_45_1","unstructured":"Alex Heye et al. \"scalable deep learning with bigdl on the urika-xc software suite\". (https:\/\/www.cray.com\/blog\/scalable-deep-learning-bigdl-urika-xc-software-suite\/).  Alex Heye et al. \"scalable deep learning with bigdl on the urika-xc software suite\". (https:\/\/www.cray.com\/blog\/scalable-deep-learning-bigdl-urika-xc-software-suite\/)."},{"key":"e_1_3_2_1_46_1","unstructured":"Shivaram Venkataraman et al. \"accelerating deep learning training with bigdl and drizzle on apache spark\". (https:\/\/rise.cs.berkeley.edu\/blog\/accelerating-deep-learning-training-with-bigdl-and-drizzle-on-apache-spark\/).  Shivaram Venkataraman et al. \"accelerating deep learning training with bigdl and drizzle on apache spark\". (https:\/\/rise.cs.berkeley.edu\/blog\/accelerating-deep-learning-training-with-bigdl-and-drizzle-on-apache-spark\/)."},{"key":"e_1_3_2_1_47_1","volume-title":"SOSP'17","author":"Venkataraman S.","unstructured":"Venkataraman , S. , Panda , A., Ousterhout , K. , Armbrust , M. , Ghodsi , A. , Franklin , M.J. , Recht , B. , and Stoica , I . Drizzle: Fast and adaptable stream processing at scale in Proceedings of the 26th Symposium on Operating Systems Principles . SOSP'17 . Venkataraman, S., Panda, A., Ousterhout, K., Armbrust, M., Ghodsi, A., Franklin, M.J., Recht, B., and Stoica, I. Drizzle: Fast and adaptable stream processing at scale in Proceedings of the 26th Symposium on Operating Systems Principles. SOSP'17."},{"key":"e_1_3_2_1_48_1","unstructured":"Jason (Jinquan) Dai et al. Building large-scale image feature extraction with bigdl at jd.com. (https:\/\/software.intel.com\/en-us\/articles\/building-large-scale-image-feature-extraction-with-bigdl-at-jdcom).  Jason (Jinquan) Dai et al. Building large-scale image feature extraction with bigdl at jd.com. (https:\/\/software.intel.com\/en-us\/articles\/building-large-scale-image-feature-extraction-with-bigdl-at-jdcom)."},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"crossref","unstructured":"Liu W. Anguelov D. Erhan D. Szegedy C. Reed S.E. Fu C.-Y. and Berg A.C. Ssd: Single shot multibox detector in ECCV. (2016).  Liu W. Anguelov D. Erhan D. Szegedy C. Reed S.E. Fu C.-Y. and Berg A.C. Ssd: Single shot multibox detector in ECCV. (2016).","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.133"},{"key":"e_1_3_2_1_51_1","volume-title":"Proceedings of the 27th International Conference on Neural Information Processing Systems.","volume":"2","author":"Sutskever I.","unstructured":"Sutskever , I. , Vinyals , O., and Le , Q.V . Sequence to sequence learning with neural networks . in Proceedings of the 27th International Conference on Neural Information Processing Systems. Vol. 2 . NIPS'14. Sutskever, I., Vinyals, O., and Le, Q.V. Sequence to sequence learning with neural networks. in Proceedings of the 27th International Conference on Neural Information Processing Systems. Vol. 2. NIPS'14."},{"key":"e_1_3_2_1_52_1","volume-title":"Proceedings of the 28th International Conference on Neural Information Processing Systems.","volume":"1","author":"Shi X.","unstructured":"Shi , X. , Chen , Z., Wang , H. , Yeung , D.-Y. , Wong , W.-k. , and Woo , W . -c. Convolutional lstm network: A machine learning approach for precipitation nowcasting . in Proceedings of the 28th International Conference on Neural Information Processing Systems. Vol. 1 . NIPS'15. Shi, X., Chen, Z., Wang, H., Yeung, D.-Y., Wong, W.-k., and Woo, W.-c. Convolutional lstm network: A machine learning approach for precipitation nowcasting. in Proceedings of the 28th International Conference on Neural Information Processing Systems. Vol. 1. NIPS'15."},{"key":"e_1_3_2_1_53_1","unstructured":"Rajiv Shah. Gigaspaces integrates insightedge platform with intel's bigdl for scalable deep learning innovation. (https:\/\/www.gigaspaces.com\/blog\/gigaspaces-to-demo-with-intel-at-strata-data-conference-and-microsoft-ignite\/).  Rajiv Shah. Gigaspaces integrates insightedge platform with intel's bigdl for scalable deep learning innovation. (https:\/\/www.gigaspaces.com\/blog\/gigaspaces-to-demo-with-intel-at-strata-data-conference-and-microsoft-ignite\/)."},{"key":"e_1_3_2_1_54_1","unstructured":"Apache Kafka. (https:\/\/kafka.apache.org\/).  Apache Kafka. (https:\/\/kafka.apache.org\/)."},{"key":"e_1_3_2_1_55_1","volume-title":"Discretized streams: fault-tolerant streaming computation at scale in The Twenty-Fourth ACM Symposium on Operating Systems Principles. (2013) SOSP'13","author":"Matei Zaharia Tathagata Das","unstructured":"Matei Zaharia , Tathagata Das , Haoyuan Li , Timothy Hunter , Scott Shenker , and Ion Stoica . Discretized streams: fault-tolerant streaming computation at scale in The Twenty-Fourth ACM Symposium on Operating Systems Principles. (2013) SOSP'13 . Matei Zaharia, Tathagata Das, Haoyuan Li, Timothy Hunter, Scott Shenker, and Ion Stoica. Discretized streams: fault-tolerant streaming computation at scale in The Twenty-Fourth ACM Symposium on Operating Systems Principles. (2013) SOSP'13."}],"event":{"name":"SoCC '19: ACM Symposium on Cloud Computing","location":"Santa Cruz CA USA","acronym":"SoCC '19","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGOPS ACM Special Interest Group on Operating Systems"]},"container-title":["Proceedings of the ACM Symposium on Cloud Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3357223.3362707","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3357223.3362707","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:13:44Z","timestamp":1750202024000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3357223.3362707"}},"subtitle":["A Distributed Deep Learning Framework for Big Data"],"short-title":[],"issued":{"date-parts":[[2019,11,20]]},"references-count":55,"alternative-id":["10.1145\/3357223.3362707","10.1145\/3357223"],"URL":"https:\/\/doi.org\/10.1145\/3357223.3362707","relation":{},"subject":[],"published":{"date-parts":[[2019,11,20]]},"assertion":[{"value":"2019-11-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}