Abstract

Modern data analytics and processing are at the heart of enterprise computing and drive advances in many scientific disciplines. In addition to designing new models and techniques for analysing the data deluge, we also need systems support that makes the analysis more performant and efficient when executed on modern and future hardware platforms.

Addressing such a challenge requires an effort that is beyong what can be typically done within a single layer of the system stack: applications are typically unaware of the run-time state of the machine and the operating system does not know what the goals of the applications are. In my talk, I will give an overview of my research on co-designing databases and operating systems and show the benefits of a holistic approach by opening the interfaces and customising the system stack for modern data processing workloads.

Bio:Jana Giceva is a Lecturer in the Department of Computing at Imperial College London. Prior to that she completed her PhD in the Systems Group at ETH Zurich, where she worked with Gustavo Alonso and Timothy Roscoe. Her research interests are in systems support for data science and Big Data to enable efficient use of modern and future hardware. The scope of her research spans multiple systems areas: from the data processing layer to operating systems, including hardware accelerators for data processing. She is the recipient of the ETH medal for her PhD dissertation awarded in 2017 and the Google European PhD Fellowship in operating systems in 2014.