IEEE 21st Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM 2013) (2013)
April 28, 2013 to April 30, 2013
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/FCCM.2013.18
Louis Woods , Dept. of Comput. Sci., ETH Zurich, Zurich, Switzerland
Gustavo Alonso , Dept. of Comput. Sci., ETH Zurich, Zurich, Switzerland
Jens Teubner , Dept. of Comput. Sci., DBIS Group, Tech. Univ. Dortmund, Dortmund, Germany
Due to stagnant clock speeds and high power consumption of commodity microprocessors, database vendors have started to explore massively parallel co-processors such as FPGAs to further increase performance. A typical approach is to push simple but compute-intensive operations (e.g., prefiltering, (de)compression) to FPGAs for acceleration. In this paper, we show how a significantly more complex operation- the computation of the skyline-can be holistically implemented on an FPGA. A skyline query computes the pareto optimal set of multi-dimensional data points. These queries have been studied in software extensively over the last decade but this paper is the first to examine skyline computation in hardware. We propose a methodology that interleaves data storage and computation, allowing multiple operations to be executed on the same working set in parallel, while accounting for all data dependencies. Our experiments show that we achieve very promising results compared to CPU-based solutions.
Bridges, Field programmable gate arrays, Pipelines, Databases, Hardware, Throughput, Pareto optimization
L. Woods, G. Alonso and J. Teubner, "Parallel Computation of Skyline Queries," Field-Programmable Custom Computing Machines, Annual IEEE Symposium on(FCCM), Seattle, WA, USA USA, 2014, pp. 1-8.