Adaptive Multi-Resolution Data Structure for Large-Scale Visualization and Modeling of Multi-Scale Geological Processes.

Numerical modeling of geological phenomena frequently requires dealing with processes of significantly different scales. Wavelets provide a convenient and efficient approach to resolving such processes, which would be hard-pressed to be solved by conventional finite-difference techniques. The system of nonlinear partial differential equations can be solved on an adaptive grid using wavelet based algorithms. The relevant features of the obtained datasets can be efficiently extracted by wavelet-based visualization and analysis tools. However, the efficiency of visualization tools as well as the efficiency of adaptive solvers strongly depends on the access time to the large datasets. We are presenting an effective data-structure for multi-resolution adaptive grids. Tree-like structure provides rapid access to the grid nodes both in sequential and parallel implementations.