Nanosurveyor: a framework for real-time data processing

Author:

Daurer Benedikt J.,Krishnan Hari,Perciano Talita,Maia Filipe R. N. C.,Shapiro David A.,Sethian James A.,Marchesini StefanoORCID

Abstract

Abstract Background The ever improving brightness of accelerator based sources is enabling novel observations and discoveries with faster frame rates, larger fields of view, higher resolution, and higher dimensionality. Results Here we present an integrated software/algorithmic framework designed to capitalize on high-throughput experiments through efficient kernels, load-balanced workflows, which are scalable in design. We describe the streamlined processing pipeline of ptychography data analysis. Conclusions The pipeline provides throughput, compression, and resolution as well as rapid feedback to the microscope operators.

Funder

Office of Science

Basic Energy Sciences

Swedish Research Council

Swedish Foundation for Strategic Research

Publisher

Springer Science and Business Media LLC

Subject

Spectroscopy,Radiology Nuclear Medicine and imaging,Chemical Engineering (miscellaneous)

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Contrast – a lightweight Python framework for beamline orchestration and data acquisition;Journal of Synchrotron Radiation;2021-06-08

2. Tomographic Reconstruction of Dynamic Features with Streaming Sliding Subsets;2020 IEEE/ACM 2nd Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing (XLOOP);2020-11

3. Ptychography at the Linac Coherent Light Source in a parasitic geometry;Journal of Applied Crystallography;2020-09-08

4. Priority research directions for in situ data management: Enabling scientific discovery from diverse data sources;The International Journal of High Performance Computing Applications;2020-03-27

5. Correlative conventional scanning and ptychographic soft x-ray microscopy;X-Ray Nanoimaging: Instruments and Methods IV;2019-09-09

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