The Wisconsin ecoDB project


The focus of the Wisconsin ecoDB project is to understand the design decisions and tradeoffs in developing energy-efficient data processing systems. We also want to design, implement and evaluate various techniques, including pure software-based mechanisms and combinations of hardware and software-based mechanisms. The overall goal is optimize the energy-efficiency of data processing systems dramatically over the current state-of-the-art. A key aspect of this project, driven by recent hardware trends, is to first find ways to use modern hardware efficiently for data processing (as that is often the easiest way to also improve the energy efficiency!)

People and Collaborators


Query Processing on Smart SSDs: Opportunities and Challenges, J. Do, Y. Kee, J. M. Patel, C. Park, K. Park, D. J. DeWitt, SIGMOD (Industrial Track) 2013.
Towards Multi-Tenant Performance SLOs, W. Lang, S. Shankar, J. M. Patel, A. Kalhan, ICDE 2012.
Wimpy Node Clusters: What About Non-Wimpy Workloads?, W. Lang, J. M. Patel and S. Shankar, DaMoN 2010.
On Energy Management, Load Balancing and Replication, W. Lang, J. M. Patel and J. F. Naughton, SIGMOD Record 2010 Extended Version.
Towards Eco-friendly Database Management Systems, W. Lang and J. M. Patel, CIDR 2009.
Join Processing for Flash SSDs: Remembering Past Lessons, J. Do and J. M. Patel, DaMoN 2009. [Best Paper Award]


This project is funded by a grant from the National Science Foundation, under grant III 0963993. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.