Petascale visualization: Approaches and initial results
Petascale visualization: Approaches and initial results
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Petascale 可视化：方法和初步结果
DOI：
10.1109/ultravis.2008.5154060
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
A. McPherson
中科院分区：
文献类型：
--
作者：
J. Ahrens;Li;B. Nouanesengsy;J. Patchett;A. McPherson
随着第一个Petascale超级计算机，Los Alamos的Roadrunner的出现，迫切需要解决如何可视化Petascale数据。 Petascale可视化性能问题的关键是交互式渲染，因为它是可视化过程中最密集的部分。对于Terascale平台，使用图形处理器（GPU）的商品簇已用于交互式渲染。对于Petascale平台，可视化和渲染可能能够在超级计算机平台本身上有效运行。在这项工作中，我们评估了多核CPU和基于GPU的处理器的渲染性能。为了实现多核处理器的高性能，我们使用多核优化的射线座引擎进行了测试以进行渲染。为了进行现实世界的性能测试，并准备佩斯卡尔可视化任务，我们将这些渲染引擎与VTK和Paraview相连。初始结果表明，针对多核CPU处理器进行优化的渲染软件为GPU提供了竞争性能，以平行大量数据的并行渲染。当前的架构多核趋势表明，基于多核的超级计算机能够现在和将来提供交互式可视化和渲染支持。
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.