Solving nearest neighbors problem on GPU to speed up the Fruchterman-Reingold graph layout algorithm

Fast searching of the nearest neigbors in unordered point clouds is a very common task. This article presents a new parallel method tested on graph layout algorithm. Graphs in computer science are widely used in social network analysis, computer networks, transportation networks, and many other areas. In general, they can visualize relationships between objects. However, fast drawing of graphs with readable layouts is still a challenge. This paper describes a novel variant of the Fruchterman-Reingold graph layout algorithm which is adapted to GPU parallel architecture using a new K-NN approach based on space-filling curves and a new way of repulsive forces computation on GPU. The paper contains both performance and quality tests of the algorithm.