A Sorting Classification of Parallel Rendering
IEEE Computer Graphics and Applications
Optimized view frustum culling algorithms for bounding boxes
Journal of Graphics Tools
WireGL: a scalable graphics system for clusters
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Chromium: a stream-processing framework for interactive rendering on clusters
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Scalable Rendering on PC Clusters
IEEE Computer Graphics and Applications
A Load-Balancing Strategy for Sort-First Distributed Rendering
SIBGRAPI '04 Proceedings of the Computer Graphics and Image Processing, XVII Brazilian Symposium
High-Quality Hardware-Based Ray-Casting Volume Rendering Using Partial Pre-Integration
SIBGRAPI '05 Proceedings of the XVIII Brazilian Symposium on Computer Graphics and Image Processing
IEEE Computer Graphics and Applications
Multi-GPU sort-last volume visualization
EG PGV'08 Proceedings of the 8th Eurographics conference on Parallel Graphics and Visualization
Proceedings of the ACM International Conference on Interactive Tabletops and Surfaces
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Recent accomplishments in the computer simulation of black oil reservoirs have created a demand for the visualization of very large models. In this paper, we present a distributed system for the rendering of such models. Following recent trends in the high performance computing area, the system is intended to make the visualization of these models available to lightweight clients on corporate networks, through the use of a cluster of inexpensive off-the-shelf PCs equipped with multiple GPUs. The proposed system uses a sort-last approach and supports a diverse set of visualization techniques. Through an efficient use of each GPU and a partial composition stage on each cluster node, our solution tackles the scalability issues that arise when using mid-to-large GPU clusters. Experimental results show that our implementation can sustain the visualization of models with up to 60 million cells at interactive rates, using a cluster with 16 nodes, each one equipped with 4 GPUs. Experimental results also demonstrate the scalability of the proposed solution.