一种以GPU异构计算为基础在簇结构中加速R树索引的方法

With the informatization development of the society, the capacity of the external memory is growing rapidly but performance is growing slower. For this reason, a variety of tree index structures have been proposed to improve the response speed of data at a limited reading and writing speed. However the discreteness of data is still hindering the further improvement of performance. Meanwhile GPU performance developing shows another direction of computer development: heterogeneous computing. With heterogeneous computing we propose a kind of parallel R-tree to handle uniform data structure and prove that its performance is better than triditional R-tree by experiment.