Power Overwhelming: Quantifying the Energy Cost of Visualisation

C. Müller, Moritz Heinemann, D. Weiskopf, T. Ertl
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Abstract

GPUs are the power-hungry tool of many visualisation researchers. However, their energy consumption has mostly been investigated outside the visualisation community, albeit our algorithms can generate more complex workloads than compute kernels. Additionally, a raising number of web-based visualisations potentially makes consumers other than the GPU more relevant. We present measurement setups for quantifying the energy cost of visualisation, ranging from software sensors over external power meters and micro controller-based setups to using oscilloscopes. These setups cover energy consumption of GPUs, CPUs and other components of a computing system. Using raycasting of spherical glyphs, volume rendering and D3 visualisations as examples, we show that there are viable options for evaluating most kinds of visualisations. We conclude by stating the challenges to a broader application of these techniques and by making recommendations on how to overcome these.
压倒性的力量:量化可视化的能量成本
gpu是许多可视化研究人员的耗电工具。然而,尽管我们的算法可以生成比计算内核更复杂的工作负载,但它们的能耗主要是在可视化社区之外进行调查的。此外,越来越多的基于网络的可视化可能会让GPU以外的消费者变得更加相关。我们提出了用于量化可视化能源成本的测量设置,范围从外部功率计的软件传感器和基于微控制器的设置到使用示波器。这些设置涵盖了gpu、cpu和计算系统其他组件的能耗。以球面符号的光线投射、体渲染和D3可视化为例,我们展示了评估大多数可视化的可行选择。最后,我们陈述了这些技术更广泛应用所面临的挑战,并就如何克服这些挑战提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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