Summary form only given. The tremendous amount of data generated by large-scale, parallel scientific and engineering simulations make the archive and analysis of this data difficult. To address this problem we, in previous work, developed an efficient archival scheme based on the functional representation of simulation data-this approximation scheme can reduce storage requirement significantly. However, common visualization tools such as the marching cubes algorithm for isosurface generation cannot be directly applied in this representation. Thus, we propose a new efficient isosurface visualization approach that takes full advantage of the functional approximation of simulation data. This method is fundamentally different from the marching cubes approach in that the visualization of isosurfaces is achieved through the solution of sets of ordinary differential equations. We present computational results detailing the effectiveness of this new approach for a simulation modeling the fluid dynamics of a turbulent reacting flow. The results demonstrate that the method is efficient in a parallel environment and represents a promising approach for the visualization of isosurfaces in simulation data from large-scale scientific applications.
['Chuang Li', 'Paul E. Plassmann']
An efficient parallel algorithm for isosurface visualization from large-scale scientific simulation data