Many emerging Big Data problems are in fact "Fast Big Data problems" where data has to be accessed with very low response time. The rise of in-memory platforms like Apache Spark is an indication of this trend. However most existing distributed in memory platforms such as Apache Spark rely on the system layer that isn't built for high performance in-memory processing. In addition, the existing system software doesn’t optimally use the parallelism inherent in the new architectures where we have CPUs with many cores and SSDs with many flash channels. Other issues such as persistence and uniform access to a large memory space in the cluster also need a fundamental rethinking.
Steffen is principal software engineer at Levyx where he works on a persistent high-performance key-value store.
Prior to joining Levyx, Steffen was postdoctoral researcher and lecturer at the Center for Embedded and Cyber-physical Systems (CECS) at UC Irvine. Steffen received his PhD in Computer Engineering from the Brandenburg University of Technology at Cottbus (BTU) in Germany, following his work at the IHP Microelectronics research institute in Frankfurt (Oder), Germany, where he worked on the design of energy-efficient hardware and software systems to enable trustworthy IoT. Steffen's work was followed with more than 40 reviewed journal, conference and workshop papers, and six registered international patents.