Cph CT Toolbox: A performance evaluation

J. Bardino, Martin Rehr, B. Vinter
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引用次数: 2

Abstract

With the first version of the Cph CT Toolbox released and introduced, we turn to intensively evaluating the performance of the FDK and Katsevich reconstruction implementations in the second major release. The evaluation focuses on comparisons between different hardware platforms from the two major GPU compute vendors, AMD and NVIDIA, using our updated CUDA and new OpenCL implementations. Such a performance comparison is in itself interesting in a narrow CT scanning and reconstruction perspective, but it also sheds some light on the performance of those AMD and NVIDIA platforms and GPU technologies: something of general interest to anyone building or considering GPU solutions for their scientific calculations. Results from the best system reveals the chosen streaming strategy to scale linearly up to problem sizes one order of magnitude larger than the available GPU memory, and with only a minor scaling decrease when increasing the problem size further to the next order of magnitude.
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Cph CT工具箱:性能评估
随着第一个版本的Cph CT工具箱的发布和介绍,我们转向在第二个主要版本中集中评估FDK和Katsevich重建实现的性能。评估侧重于比较来自两大主要GPU计算供应商AMD和NVIDIA的不同硬件平台,使用我们更新的CUDA和新的OpenCL实现。从狭窄的CT扫描和重建角度来看,这样的性能比较本身就很有趣,但它也揭示了AMD和NVIDIA平台和GPU技术的性能:对于那些正在构建或考虑为其科学计算构建GPU解决方案的人来说,这是一个普遍感兴趣的东西。来自最佳系统的结果显示,所选择的流策略可以线性扩展到比可用GPU内存大一个数量级的问题大小,并且当将问题大小进一步增加到下一个数量级时,只会有轻微的缩放减少。
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