Performance Modeling of Spatio-Temporal Algorithms Over GEDS Framework
International Journal of Grid and High Performance Computing
Stream-Mode FPGA acceleration of complex pattern trajectory querying
SSTD'13 Proceedings of the 13th international conference on Advances in Spatial and Temporal Databases
GEDS: GPU execution of spatio-temporal queries over spatio-temporal data streams
Journal of Embedded Computing
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Much research exists for the efficient processing of spatio-temporal data streams. However, all methods ultimately rely on an ill-equipped processor [22], namely a CPU, to evaluate concurrent, continuous spatio-temporal queries over these data streams. This paper presents GEDS, a scalable, Graphics Processing Unit (GPU)-based framework for the evaluation of continuous spatio-temporal queries over spatio-temporal data streams. GEDS employs the computation sharing and parallel processing paradigms to deliver scalability in the evaluation of continuous spatio-temporal queries. The GEDS framework utilizes the parallel processing capability of the GPU, a stream processor by trade, to handle the computation required in this application. Experimental evaluation shows promising performance and shows the scalability and efficacy of GEDS in spatio-temporal data streaming environments.