{"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/real-time-machine-learning-the-missing-pieces","title":"Real-Time Machine Learning: The Missing Pieces","arxiv_id":"1703.03924","date":"2017-03-11","proceeding":null,"authors":["Robert Nishihara","Philipp Moritz","Stephanie Wang","Alexey Tumanov","William Paul","Johann Schleier-Smith","Richard Liaw","Mehrdad Niknami","Michael. I. Jordan","Ion Stoica"],"abstract":"Machine learning applications are increasingly deployed not only to serve\npredictions using static models, but also as tightly-integrated components of\nfeedback loops involving dynamic, real-time decision making. These applications\npose a new set of requirements, none of which are difficult to achieve in\nisolation, but the combination of which creates a challenge for existing\ndistributed execution frameworks: computation with millisecond latency at high\nthroughput, adaptive construction of arbitrary task graphs, and execution of\nheterogeneous kernels over diverse sets of resources. We assert that a new\ndistributed execution framework is needed for such ML applications and propose\na candidate approach with a proof-of-concept architecture that achieves a 63x\nperformance improvement over a state-of-the-art execution framework for a\nrepresentative application.","url_abs":"http://arxiv.org/abs/1703.03924v2","url_pdf":"http://arxiv.org/pdf/1703.03924v2.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":"real-time-machine-learning-the-missing-pieces","repo_url":"https://github.com/AmeerHajAli/ray2","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"real-time-machine-learning-the-missing-pieces","repo_url":"https://github.com/flow-project/ray","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"decision-making","task_name":"Decision Making"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1703.03924","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}