Gpu-based General-purpose Parallel Computational Library Design And Research

GPU is famous for its high calculation capacity and bandwidth, with the development of graphic hardware, GPU is much more powerful than ever before. General purpose computation with GPU is a hot-spot recently. Because GPU is designed for 3D graphic, so it is hard to use those resources. This paper describes how to build a library for GPU general purpose computation. This library simplifys the whole process, and maps some algorithms to GPU.Firstly, this paper introduces the modern programmable graphic hardware, then analyses the development stage and some related technology. After that it points out the useful resources for calculation by researching the structure of graphic hardware.Secondly, this paper analyses the workflow and functions of OpenGL and GLSL. Though analysis to graphic API and graphic hardwares, it points out the data organization, output method and workflow in the graphic hardware for general computation; describes the step and method in detal. After that, this paper constructs a platform for GPU parall computation. With this platform, programming could be greatly simplified.Thirdly, this paper offers a way to map some algorithms to GPU, such as addition, subtraction, multiplication, max, min, sorting and FFT. Each GPU algorithm method and core shader code for GPU programming model is described in detail. After that those GPU algorithms are compared with the corresponding algorithms on CPU. Three environments were used to test those algorithms. The result shows the advantage, disadvantage and bottleneck of graphic hardware. Algorithms with a certain parallelism and a large amount of computation such as matrix multiplication, sorting and FFT could get a better performance on GPU.At last, the latest generation graphic hardware and its general-purpose-designed driver are introduced.