基于CUDA的加速Laue深度重建算法

Ke Yue, N. Schwarz, J. Tischler
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引用次数: 1

摘要

劳厄衍射显微实验采用多色劳厄微衍射技术,在所有三维空间上以亚微米的空间分辨率检测材料的结构。在实验过程中,测量局部晶体取向、取向梯度和应变作为性能,并将其记录在HDF5图像格式中。记录的图像将使用深度重建算法进行处理,以便于未来的数据分析。但目前的深度重建算法处理时间较长,单次实验采集的数据重建可能需要2周的时间。为了提高深度重建的计算速度,本文提出了一种可扩展的GPU深度重建方案。测试结果表明,对于不同大小的输入数据,运行时间将比以前的CPU设计快10到20倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Accelerating Laue Depth Reconstruction Algorithm with CUDA
The Laue diffraction microscopy experiment uses the polychromatic Laue micro-diffraction technique to examine the structure of materials with sub-micron spatial resolution in all three dimensions. During this experiment, local crystallographic orientations, orientation gradients and strains are measured as properties which will be recorded in HDF5 image format. The recorded images will be processed with a depth reconstruction algorithm for future data analysis. But the current depth reconstruction algorithm consumes considerable processing time and might take up to 2 weeks for reconstructing data collected from one single experiment. To improve the depth reconstruction computation speed, we propose a scalable GPU program solution on the depth reconstruction problem in this paper. The test result shows that the running time would be 10 to 20 times faster than the prior CPU design for various size of input data.
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