GPU Based Improved Fast Iterative Algorithm for Eikonal Equation

In this paper we propose an improved fast iterative method to solve the Eikonal equation, which can be implemented in parallel. We improve the fast iterative method for Eikonal equation in two novel ways, in the value update and in the error correction. The new value update is very similar to the fast iterative method in that we selectively update the points in the active list chosen by a convergence measure. However, in order to save time, the improved algorithm does not do a convergence check of the neighboring points of the narrow band as the fast iterative method does. The additional error correction step is to correct the errors that the previous value update step may cause. The error correction step consists of finding and recalculating the point values in a separate remedy list which is quite easy to implement on a GPU. In contrast to the fast marching method and the fast sweeping method for the Eikonal equation, our improved method does not need to compute the solution with any special ordering in either the remedy list or the active list so that it can be implemented in parallel. In our experiments, we implemented our new algorithm in parallel on a GPU and compared the elapsed time with other current algorithms. The improved fast iterative method runs faster than the other algorithms in most cases in our experiments.