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 wins Google Focused Research Award September 24, 2018
- ACM SIGSPATIAL Best Paper Award for DIAS Researchers September 17, 2018
- DIAS Scientist Wins Chorafas Award September 10, 2018
- Anastasia Ailamaki Wins Nemitsas Prize September 3, 2018
- EPFL Authors Shine at DSN-2018 July 24, 2018