Distributed X-ray photon correlation spectroscopy data reduction using Hadoop MapReduce

被引:15
作者
Khan, Faisal [1 ]
Narayanan, Suresh [1 ]
Sersted, Roger [2 ]
Schwarz, Nicholas [1 ]
Sandy, Alec [1 ]
机构
[1] Argonne Natl Lab, Xray Sci Div, 9700 South Cass Ave, Lemont, IL 60439 USA
[2] Argonne Natl Lab, APS Engn Support, 9700 South Cass Ave, Lemont, IL 60439 USA
关键词
multi-speckle X-ray photon correlation spectroscopy; XPCS; MapReduce; parallel implementation; Advanced Photon Source; SPECKLE VISIBILITY SPECTROSCOPY; SCATTERING; DETECTOR;
D O I
10.1107/S160057751800601X
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
Multi-speckle X-ray photon correlation spectroscopy (XPCS) is a powerful technique for characterizing the dynamic nature of complex materials over a range of time scales. XPCS has been successfully applied to study a wide range of systems. Recent developments in higher-frame-rate detectors, while aiding in the study of faster dynamical processes, creates large amounts of data that require parallel computational techniques to process in near real-time. Here, an implementation of the multi-tau and two-time autocorrelation algorithms using the Hadoop MapReduce framework for distributed computing is presented. The system scales well with regard to the increase in the data size, and has been serving the users of beamline 8-ID-I at the Advanced Photon Source for near real-time autocorrelations for the past five years.
引用
收藏
页码:1135 / 1143
页数:9
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