Development of General-purpose Large-scale Data Visualization System using Implicit Function Representation

Abstract

Physical phenomena are complex interactions among multiple fields, and numerical simulations are widely used to comprehend and predict them. With the improvements of computational capabilities, it has become feasible to perform large-scale simulations and visualizations. However, large-scale visualization poses challenges in identifying the region of interest, necessitating the interactive visualization. Particularly in coupled analyses, various discretization methods is employed depending on their application. This study proposes a general-purpose large-scale visualization system that is not depend on specific numerical analysis methodologies. It transforms computational results into implicit function representations and applies distributed-memory parallel processing to the marching cubes method. The evaluation of parallel computing performance confirms that the proposed system has reasonable parallel efficiency.