在体量分析和直接体量渲染描述符计算中实现更高的能效

Jacob D. Hauenstein, Timothy S. Newman
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引用次数: 0

摘要

本文介绍并评估了旨在提高在 x86 级设置中确定描述符(用于体积数据分析和一种常见的科学可视化模式)的能效的方法。这些方法是根据计算设置的标准方法进行评估的。总共考虑了六种提高效率的方法。其中四种基于计算。另外两种基于内存。描述符是经典的梯度和曲率描述符。除了用于体积分析外,它们还用于经典的基于光线投射的直接体积渲染 (DVR),这是本文特别关注的一个应用领域。将所描述的方法理想地结合到梯度描述符的确定中,在计算设置中只需标准方法的 80% 能量即可计算出梯度描述符;能量效率提高了 1.2 倍。对于曲率描述符的确定,所述方法的理想组合可将能效提高 2 倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Achieving Better Energy Efficiency in Volume Analysis and Direct Volume Rendering Descriptor Computation
Approaches aimed at achieving improved energy efficiency for determination of descriptors—used in volumetric data analysis and one common mode of scientific visualisation—in one x86-class setting are described and evaluated. These approaches are evaluated against standard approaches for the computational setting. In all, six approaches for improved efficiency are considered. Four of them are computation-based. The other two are memory-based. The descriptors are classic gradient and curvature descriptors. In addition to their use in volume analyses, they are used in the classic ray-casting-based direct volume rendering (DVR), which is a particular application area of interest here. An ideal combination of the described approaches applied to gradient descriptor determination allowed them to to be computed with only 80% of the energy of a standard approach in the computational setting; energy efficiency was improved by a factor of 1.2. For curvature descriptor determination, the ideal combination of described approaches achieved a factor-of-two improvement in energy efficiency.
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