Parallel multiresolution volume rendering of large data sets with error-guided load balancing

Authors:
Chaoli Wang;Jinzhu Gao;Han-Wei Shen
Affiliations:
The Ohio State University, Columbus, Ohio;The Ohio State University, Columbus, Ohio;The Ohio State University, Columbus, Ohio
Venue:
EG PGV'04 Proceedings of the 5th Eurographics conference on Parallel Graphics and Visualization
Year:
2004

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Abstract

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.