Hasso-Plattner-Institut
Prof. Dr. Tilmann Rabl
 

Viktor Leis

Affiliation: TU Munich
Title: Co-Designing Database Systems and Unikernels for the Cloud: Reimagining OS Abstractions for Modern Hardware

 

Abstract

Although the idea of custom, DBMS-optimized OS kernels is old, it is largely unrealized due to the demands of hardware compatibility and the reluctance of users to install specialized operating systems. However, the cloud and the database-as-a-service model make custom OS kernels realistic for the first time. Among specialized OS kernel architectures, unikernels stand out for relying on a single address space, eliminating the need for costly process isolation that is provided by general-purpose operating systems. They offer benefits such as the elimination of system call overhead, direct access to hardware, and reduced complexity. Beyond these immediate advantages, unikernels offer a unique opportunity: the possibility to revisit dated POSIX APIs. By allowing direct interaction with modern hardware primitives, unikernels pave the way for the development of novel abstractions that are not confined to the limitations of older APIs, opening doors to a new era of co-designed, high-performance cloud-native data processing systems and OS kernels.

Short CV

Viktor Leis is a Full Professor in the Computer Science Department at TUM, leading the chair for Decentralized Information Systems and Data Management. His research revolves around designing high-performance data management systems and includes core database systems topics such as query processing, query optimization, transaction processing, index structures, and storage. Another major research area is the architecture of cloud-native, cost-efficient information systems. Viktor Leis received his doctoral degree in 2016 from TUM and was a Professor at the Friedrich-Schiller-Universität Jena and Friedrich-Alexander-Universität Erlangen-Nürnberg before returning to TUM in 2022. He received the ACM SIGMOD dissertation award, the IEEE TCDE Rising Star Award, best paper awards at IEEE ICDE and ACM SIGMOD, and an ERC Starting Grant.