Authors/Presenters:Jiangfei Duan, The Chinese University of Hong Kong; Ziang Song, ByteDance; Xupeng Miao and Xiaoli Xi, Carnegie Mellon University; Dahua Lin, The Chinese University of Hong Kong; Harry Xu, University of California, Los Angeles; Minjia Zhang, Microsoft; Zhihao Jia, Carnegie Mellon University  Our sincere thanks to USENIX, and the Presenters & Authors for publishing their superb 21st USENIX Symposium on Networked Systems Design and Implementation (NSDI '24) content, placing the organizations enduring commitment to Open Access front and center. Originating from the conference’s events situated at the Hyatt Regency Santa Clara; and via the organizations YouTube channel.  Permalink

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The 21st USENIX Symposium on Networked Systems Design and Implementation (NSDI ’24) introduced Parcae, a system designed for proactive and liveput-optimized training of deep neural networks (DNN) on preemptible cloud instances. This presentation highlights the advantages of using preemptible instances for cost-effective and efficient DNN training.

USENIX NSDI ’24 – Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances