In-Memory Grid Files on Graphics Processors

Recently, graphics processing units, or GPUs, have become a viable alternative as commodity, parallel hardware for general-purpose computing, due to their massive data-parallelism, high memory bandwidth, and improved general-purpose programming interface. In this paper, the authors explore the use of GPU on the grid file, a traditional multidimensional access method. Considering the hardware characteristics of GPUs, they design a massively multi-threaded GPU-based grid file for static, memory-resident multidimensional point data. Moreover, they propose a hierarchical grid file variant to handle data skews efficiently. Their implementations on the NVIDIA G80 GTX graphics card are able to achieve two to eight times' higher performance than their CPU counterparts on a single PC.