End-to-end data reduction and hardware accelerated rendering techniques for visualizing time-varying non-uniform grid volume data

We present a systematic approach for direct volume rendering terascale-sized data that are time-varying, and possibly non-uniformly sampled, using only a single commodity graphics PC. Our method employs a data reduction scheme that combines lossless, wavelet-based progressive data access with a user-directed, hardware-accelerated data packing technique. Data packing is achieved by discarding data blocks with values outside the data interval of interest and encoding the remaining data in a structure that can be efficiently decoded in the GPU. The compressed data can be transferred between disk, main memory, and video memory more efficiently, leading to more effective data exploration in both spatial and temporal domains. Furthermore, our texture-map based volume rendering system is capable of correctly displaying data that are sampled on a stretched, Cartesian grid. To study the effectiveness of our technique we used data sets generated from a large solar convection simulation, computed on a non-uniform, 504×504×2048 grid.