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Speaker:
Wilfried N. Gansterer
Associate Professor, Computer Science, University of Vienna in Austria
Title:
Distributed Matrix Computations Based on Gossiping
Abstract:
We discuss novel randomized algorithms for distributed matrix computations which are based on gossip-style data aggregation. In contrast to parallel algorithms or to approaches where randomization in linear algebra problems is primarily utilized for approximation purposes, our emphasis is on the flexibility and fault tolerance which can be achieved with randomized communication schedules. In our algorithms, each node communicates only with its nearest neighbors. Thus, they are attractive for decentralized and dynamic computing networks and they can recover from various types of failures occurring at runtime.
As concrete case studies, we discuss a distributed QR factorization method and distributed orthogonal iteration method in terms of performance, resilience against hard and soft failures, and resilience against asynchrony of the nodes.
Bio:
Wilfried N. Gansterer is currently associate professor at the Faculty of Computer Science of the University of Vienna in Austria. He holds a master degree in mathematics from Vienna University of Technology, an MSc in Scientific Computing/Computational Mathematics from Stanford University, and a PhD in Scientific Computing from Vienna University of Technology. He worked as a post-doctoral research associate at the Department of Computer Science at the University of Tennessee at Knoxville. Subsequently, he joined the Faculty of Computer Science at the University of Vienna, where he received tenure in 2012. His research interests include numerical and high performance computing, parallel and distributed computing, as well as data mining and internet security.
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