A Parallel Access Method for Spatial Data Using GPU
Spatial Access Methods (SAMs) are used for information retrieval in large spatial databases. Many of the SAMs use sequential tree structures to search the result set of the spatial data which are contained in the given query region. In order to improve performance for the SAM, this paper proposes a parallel method using GPU. Since, the searching process needs intensive computation but is independently examined on a lot of the MBRs of the spatial data, the spatial search function can be efficiently computed on GPU in a massive parallel way.