论文标题

PTYCHOPY:​​PTYChographic数据分析的GPU框架

Ptychopy: GPU framework for ptychographic data analysis

论文作者

Yue, Ke, Deng, Junjing, Jiang, Yi, Nashed, Youssef, Vine, David, Vogt, Stefan

论文摘要

X射线ptychography成像,例如高级光子源(APS),涉及控制仪器硬件,以收集一组衍射模式,这些模式是从扩展样品上重叠的相干照明点,管理数据存储的重叠相干照明点,从收到的衍射模式中重建Ptychographic图像,并提供结果和馈送的结果。除了复杂的工作流程外,Ptychography仪器还可以每秒生成多达几个TB的数据,这需要实时处理。这提出了需要开发高性能,强大且用户友好的处理软件包,以进行Ptychographic数据分析。在本文中,我们提出了一个软件框架,该框架提供可视化,工作流控制和数据重建功能。为了加速计算和大型数据集过程,使用GPU上的CUDA-C使用三种算法,EPIE,DM和LSQML实现了数据重建部分。

X-ray ptychography imaging at synchrotron facilities like the Advanced Photon Source (APS) involves controlling instrument hardwares to collect a set of diffraction patterns from overlapping coherent illumination spots on extended samples, managing data storage, reconstructing ptychographic images from acquired diffraction patterns, and providing the visualization of results and feedback. In addition to the complicated workflow, ptychography instrument could produce up to several TB's of data per second that is needed to be processed in real time. This brings up the need to develop a high performance, robust and user friendly processing software package for ptychographic data analysis. In this paper we present a software framework which provides functionality of visualization, work flow control, and data reconstruction. To accelerate the computation and large datasets process, the data reconstruction part is implemented with three algorithms, ePIE, DM and LSQML using CUDA-C on GPU.

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