Parallel Multiresolution Volume Rendering of Large Data Sets with Error-Guided Load Balancing

We present a new parallel multiresolution volume rendering algorithm for visualizing large data sets. Using the wavelet transform, the raw data is first converted into a multiresolution wavelet tree. To eliminate the parent-child data dependency for reconstruction and achieve load-balanced rendering, we design a novel algorithm to partition the tree and distribute the data along a hierarchical space-filling curve with error-guided bucketization. At run time, the wavelet tree is traversed according to the user-specified error tolerance, data blocks of different resolutions are decompressed and rendered to compose the final image in parallel. Experimental results showed that our algorithm can reduce the run-time communication cost to a minimum and ensure a well-balanced workload among processors when visualizing gigabytes of data with arbitrary error tolerances. Categories and Subject Descriptors (according to ACM CCS): E.4 [Coding and Information Theory]: Data compaction and compre...

• Type: Conference
• Year: 2004
• Where: EGPGV
• Authors: Chaoli Wang, Jinzhu Gao, Han-Wei Shen
• Keywords: Computer Graphics, EGPGV 2004, Multiresolution Wavelet Tree, Visualization, Wavelet Tree