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Petascale visualization: Approaches and initial results

James Ahrens, Li-Ta Lo, Boonthanome Nouanesengsy, John Patchett, Allen McPherson
Los Alamos National Laboratory, Los Alamos, NM
Workshop on Ultrascale Visualization, 2008. UltraVis 2008

@inproceedings{ahrens2008petascale,

   title={Petascale visualization: Approaches and initial results},

   author={Ahrens, J. and Lo, L.T. and Nouanesengsy, B. and Patchett, J. and McPherson, A.},

   booktitle={Ultrascale Visualization, 2008. UltraVis 2008. Workshop on},

   pages={24–28},

   year={2008},

   organization={IEEE}

}

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With the advent of the first petascale supercomputer, Los Alamos’s Roadrunner, there is a pressing need to address how to visualize petascale data. The crux of the petascale visualization performance problem is interactive rendering, since it is the most computationally intensive portion of the visualization process. For terascale platforms, commodity clusters with graphics processors (GPUs) have been used for interactive rendering. For petascale platforms, visualization and rendering may be able to run efficiently on the supercomputer platform itself. In this work, we evaluated the rendering performance of multi-core CPU and GPU-based processors. To achieve high-performance on multi-core processors, we tested with multi-core optimized raytracing engines for rendering. For real-world performance testing, and to prepare for petascale visualization tasks, we interfaced these rendering engines with VTK and ParaView. Initial results show that rendering software optimized for multi-core CPU processors provides competitive performance to GPUs for the parallel rendering of massive data. The current architectural multi-core trend suggests multi-core based supercomputers are able to provide interactive visualization and rendering support now and in the future.
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