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Extreme Scaling of Production Visualization Software on Diverse Architectures

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8 Author(s)
Childs, H. ; Lawrence Berkeley Nat. Lab., Berkeley, CA, USA ; Pugmire, D. ; Ahern, S. ; Whitlock, B.
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This article presents the results of experiments studying how the pure-parallelism paradigm scales to massive data sets, including 16,000 or more cores on trillion-cell meshes, the largest data sets published to date in the visualization literature. The findings on scaling characteristics and bottlenecks contribute to understanding how pure parallelism will perform in the future.

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Computer Graphics and Applications, IEEE  (Volume:30 ,  Issue: 3 )