GPU Based Spot Noise Parallel Algorithm For 2D Vector Field Visualization

Modern computer technology has greatly promoted the development of visualization in scientific computing,2D vector field visualization is one of the most challenge research tasks of visualization in scientific computing。Currently, the application domain of visualization is very extensive, and almost involves all fields of thermal science and engineering.Ocean flow field visualization plays an important role in the development of ocean science, which convert the vector field data into a graphic or an image that can be analyzed, and an interactive guide and control can be implemented in computing. So it is widely used in the research of the overall information of the marine. However, with the rapid development of science and technology, the ocean vector field data collected is very large, which is a huge challenge for computing power. At present, parallel processing technology has been greatly development, and it provides a new way for interactive and real time visualization of large scale vector field data.In the past few years, the computing performance of GPU has increased rapidly. It is adapt to a high degree of parallelism and a large number of floating point computing environment because of its unique set of hardware structure. Along with the increase of the GPU programmable performance, programmable floating point unit has become the main computing power in GPU. The application of GPU competence has far exceeded the graphics rendering tasks; and it has been widely applied to accelerate non-graphics computation problems. With the strong computing power of modern GPU, exploiting the GPU to address some large scale computation problems is an inevitable trend.Spot noise is an important research method which shows the integrity and global characteristics of the marine environment. It can fully display the macro flow characteristics of the marine. But in the current study, we often face a major problem, which is the algorithm needs considerable computational time. So it is difficult to achieve the effect of real time visualization. This paper will present a GPU based spot noise parallel algorithm for 2D vector field visualization. It is implemented with parallel operations on the GPU. In this paper, cluster based spot noise parallel algorithm is used to be a reference. Through the comparison of both computing preference, GPU based parallel algorithm shows great superiority in the large scale vector field visualization. As a test case to compare the parallel performance and data processing time of the algorithms, it uses velocity field in east coast that is a 2D vector field. Experimental results show that when the parallel algorithm based on two different mechanisms maintain the same characteristics of the vector field, GPU based parallel algorithm is better, and improve the processing time more effectively. It provides an important method for interactive applications and in-time remote visualization of vector field.