Diving deep: data-management and visualization strategies for adaptive mesh refinement simulations
Michael L. Norman, John M. Shalf, Stuart Levy, Greg Daues · Computing in Science & Engineering · 1999
The authors' cosmological applications illustrate problems and solutions in storing, handling, visualizing, virtually navigating, and remote serving data produced by large scale adaptive mesh refinement simulations. The authors describe their cosmological AMR algorithm and how they applied it to star, galaxy, and galaxy cluster formation. Basically, the algorithm allows them to place very high resolution grids precisely where they are needed-where stars and galaxies condense out of diffuse gas. In these applications, AMR allows the authors to achieve a local mesh refinement, relative to the global coarse grid, of more than a factor of 10/sup 6/. Such resolution would be totally impossible to achieve with a global, uniform fine grid. Thus, AMR allows them to simulate multiscale phenomena that are out of reach with fixed grid methods.