{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/bigdl-a-distributed-deep-learning-framework","title":"BigDL: A Distributed Deep Learning Framework for Big Data","arxiv_id":"1804.05839","date":"2018-04-16","proceeding":null,"authors":["Jason Dai","Yiheng Wang","Xin Qiu","Ding Ding","Yao Zhang","Yanzhang Wang","Xianyan Jia","Cherry Zhang","Yan Wan","Zhichao Li","Jiao Wang","Shengsheng Huang","Zhongyuan Wu","Yang Wang","Yuhao Yang","Bowen She","Dongjie Shi","Qi Lu","Kai Huang","Guoqiong Song"],"abstract":"This paper presents BigDL (a distributed deep learning framework for Apache Spark), which has been used by a variety of users in the industry for building deep learning applications on production big data platforms. It allows deep learning applications to run on the Apache Hadoop/Spark cluster so as to directly process the production data, and as a part of the end-to-end data analysis pipeline for deployment and management. Unlike existing deep learning frameworks, BigDL implements distributed, data parallel training directly on top of the functional compute model (with copy-on-write and coarse-grained operations) of Spark. We also share real-world experience and \"war stories\" of users that have adopted BigDL to address their challenges(i.e., how to easily build end-to-end data analysis and deep learning pipelines for their production data).","url_abs":"https://arxiv.org/abs/1804.05839v4","url_pdf":"https://arxiv.org/pdf/1804.05839v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"bigdl-a-distributed-deep-learning-framework","repo_url":"https://github.com/depexo/BigDL-master","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"fraud-detection","task_name":"Fraud Detection"},{"task_slug":"management","task_name":"Management"},{"task_slug":"object-detection","task_name":"Object Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1804.05839","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}