Gesellschaft für Informatik e.V.

Lecture Notes in Informatics

Datenbanksysteme für Business, Technologie und Web (BTW) 2013 - Workshopband P-216, 17-26 (2013).

Gesellschaft für Informatik, Bonn

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Stream join processing on heterogeneous processors

Tomas Karnagel , Benjamin Schlegel , Dirk Habich and Wolfgang Lehner


The window-based stream join is an important operator in all data streaming systems. It has often high resource requirements so that many efficient sequential as well as parallel versions of it were proposed in the literature. The parallel stream join operators recently gain increasing interest because hardware is getting more and more parallel. Most of these operators, however, are only optimized for processors with homogeneous execution units (e.g., multi-core processors). Newly available processors with heterogeneous execution units cannot be exploited whereas such processors provide typically a very high peak performance. In this paper, we propose an initial variant of a window-based stream join operator that is optimized for processors with heterogeneous execution units. We provide an efficient load balancing approach to utilize all available execution units of a processor and further provide highly-optimized kernels that run on them. On our test machine with a 4-core CPU and an integrated graphics processor, our operator achieves a speedup of 69 2x compared to our single-threaded . implementation.

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Gesellschaft für Informatik, Bonn
ISBN 978-3-88579-610-7

Last changed 12.03.2014 15:16:21