Wednesday, February 27, 2019 12:15 PM EST
Alexey Karyakin, PhD candidate
David R. Cheriton School of Computer Science
Energy consumed by the main memory in existing database systems does not effectively scale down with lower system utilization, both in terms of actual memory usage and load conditions. At the same time, main memory represents a sizable portion of the total server energy footprint, which makes it an outlier as the rest of the system moves towards energy proportionality.
We introduce DimmStore, a prototype main-memory database system that addresses the problem of memory energy consumption.
Wednesday, February 13, 2019 12:15 PM EST
Chang Ge, PhD candidate
David R. Cheriton School of Computer Science
Organizations are increasingly interested in allowing external data scientists to explore their sensitive datasets. Due to the popularity of differential privacy, data owners want the data exploration to ensure provable privacy guarantees. However, current systems for differentially private query answering place an inordinate burden on the data analysts to understand differential privacy, manage their privacy budget and even implement new algorithms for noisy query answering. Moreover, current systems do not provide any guarantees to the data analyst on the quantity they care about, namely accuracy of query answers.
