论文标题
加速使用CUDA的LAUE深度重建算法
Accelerating Laue Depth Reconstruction Algorithm with CUDA
论文作者
论文摘要
LAUE衍射显微镜实验使用多色LAUE微划分技术来检查所有三个维度在所有三个维度上具有亚微米空间分辨率的材料的结构。在此实验中,局部晶体学取向,方向梯度和应变作为特性,将以HDF5图像格式记录。记录的图像将使用深度重建算法进行处理,以进行将来的数据分析。但是,当前的深度重建算法会消耗相当大的处理时间,并且可能需要长达2周的时间来重建从一个实验中收集的数据。为了提高深度重建计算速度,我们在本文中提出了有关深度重建问题的可扩展GPU程序解决方案。测试结果表明,对于各种输入数据,运行时间将比以前的CPU设计快10到20倍。
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.