PyNX: high-performance computing toolkit for coherent X-ray imaging based on operators

被引:38
|
作者
Favre-Nicolin, Vincent [1 ,2 ]
Girard, Gaetan [1 ,3 ]
Leake, Steven [1 ]
Carnis, Jerome [4 ]
Chushkin, Yuriy [1 ]
Kieffer, Jerome [1 ]
Paleo, Pierre [1 ]
Richard, Marie-Ingrid [1 ,2 ,3 ]
机构
[1] European Synchrotron, ESRF, 71 Ave Martyrs, F-38000 Grenoble, France
[2] Univ Grenoble Alpes, Grenoble, France
[3] CEA, IRIG MEM, Nanostruct & Synchrotron Radiat Lab, F-38000 Grenoble, France
[4] DESY, D-22607 Hamburg, Germany
来源
JOURNAL OF APPLIED CRYSTALLOGRAPHY | 2020年 / 53卷 / 53期
关键词
coherent X-ray imaging; ptychography; coherent diffraction imaging; graphical processing units; PHASE; ALGORITHM; STRAIN; FIELD;
D O I
10.1107/S1600576720010985
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The open-source PyNX toolkit has been extended to provide tools for coherent X-ray imaging data analysis and simulation. All calculations can be executed on graphical processing units (GPUs) to achieve high-performance computing speeds. The toolkit can be used for coherent diffraction imaging (CDI), ptychography and wavefront propagation, in the far- or near-field regime. Moreover, all imaging operations (propagation, projections, algorithm cycles...) can be implemented in Python as simple mathematical operators, an approach which can be used to easily combine basic algorithms in a tailored chain. Calculations can also be distributed to multiple GPUs, e.g. for large ptychography data sets. Command-line scripts are available for on-line CDI and ptychography analysis, either from raw beamline data sets or using the coherent X-ray imaging data format.
引用
收藏
页码:1404 / 1413
页数:10
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