The emergence of global-scale online services has galvanized scale-out software, characterized by splitting vast datasets and massive computation across many independent servers. In a paper appearing in ASPLOS 2012, Profs. Ailamaki and Falsafi and their teams identify the inefficiencies in modern server processors and memory systems when running emerging scale-out workloads (e.g., analytics, data serving, debugging as a service, video streaming and web) and advocate server chip architectures and hardware mechanisms that maximize silicon efficiency for these workloads. For more information see, Clearing the Clouds: A Study of Emerging Workloads on Modern Hardware by Ferdman et al., available as an EPFL Tech. Report.
- Martin Jaggi Co-chairs Applied Machine Learning Days April 25, 2017
- Swiss Radio and TV Station RTS 1 Hosts Martin Jaggi April 24, 2017
- 2017 EcoCloud Annual Event around the Corner April 24, 2017
- David Atienza Chairs a Successful DATE 2017 Conference April 19, 2017
- Martin Jaggi Wins 2016 Google Faculty Research Award April 11, 2017