A Sorting Classification of Parallel Rendering
IEEE Computer Graphics and Applications
Parallel volume ray-casting for unstructured-grid data on distributed-memory architectures
PRS '95 Proceedings of the IEEE symposium on Parallel rendering
PRS '97 Proceedings of the IEEE symposium on Parallel rendering
ZSWEEP: an efficient and exact projection algorithm for unstructured volume rendering
VVS '00 Proceedings of the 2000 IEEE symposium on Volume visualization
Optical Models for Direct Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
Hardware-Assisted Visibility Sorting for Unstructured Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
UberFlow: a GPU-based particle engine
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Hierarchical visualization and compression of large volume datasets using GPU clusters
EG PGV'04 Proceedings of the 5th Eurographics conference on Parallel Graphics and Visualization
A scalable, hybrid scheme for volume rendering massive data sets
EG PGV'06 Proceedings of the 6th Eurographics conference on Parallel Graphics and Visualization
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Large-scale numerical simulation produces datasets with ever-growing size and complexity. In particular, unstructured meshes are encountered in many applications. Volume rendering provides a way to efficiently analyze such datasets. Recent advances in graphics hardware have enabled the implementation of efficient unstructured volume rendering algorithms on the GPU. However, GPU architecture limitations make these methods difficultly amenable to a parallel implementation, which is necessary to render very large datasets at interactive speeds and high resolutions. Many previous parallel approaches have focused on softwarebased algorithms. In this paper, we present a hybrid object-space/image-space CPU-GPU distributed parallel volume rendering method, taking advantage of the flexibility afforded by the CPU, including SIMD processing capabilities, and using GPUs to perform repetitive tasks like depth-sorting and compositing. We present the impact of the different phases on the overall rendering time as a function of node number.