The project aims to develop an infrastructure that would enable users to input data about an individual student and receive back information about the student’s risk profile and the likelihood of responding to a particular intervention. We will leverage Red Hat MPC...
The emergence of cloud-computing, coupled with the shift of processing intelligence towards the very network edge has lowered the bar for private edge use at scale. However, the approach of simply increasing the capacity at the edge does not unlock the full promise of...
Auto-scaling mechanisms are an important line of defense against distributed denial of service (DDoS) attacks in the cloud. Using auto-scaling, machines can be added and removed in an online manner to respond to fluctuating load. It is commonly believed that the...
Note: See the Near-Data Data Transformation project page for information about the work that led to this project. Abstract: Data movement through the memory hierarchy is a fundamental bottleneck for computing systems. A key reason is that data access patterns do not...
Note: Please see the Robust Data Systems Tuning project page for earlier results associated with this research. Abstract: Data systems’ performance is tuned via analytical cost models that take into account all tuning knobs and predict performance....
