I/O optimized multiresolution data organization

Large scale simulation data challenges the ability of visualization. It becomes an important research content that how to reorganize the large scale data into multiresolution representation and improve the interactive performance of visualization. Considering the data block size produced by large scale simulation mismatches the need of visualization. A novel parallel algorithm of I/O optimized multiresolution data organization is introduced, and it reorganizes simulation data with lower memory need into multiresolution form which matching the optimized I/O size. This technique has been tested on large scale simulation data, its output performance is better than directly parallel write, and interactive visualization performance improves significantly.