학술논문

Distributed X‐ray photon correlation spectroscopy data reduction using Hadoop MapReduce.
Document Type
Article
Source
Journal of Synchrotron Radiation. Jul2018, Vol. 25 Issue 4, p1135-1143. 8p.
Subject
*LIGHT beating spectroscopy
*DATA reduction
*AUTOCORRELATION (Statistics)
*DISTRIBUTED computing
*PARALLEL programs (Computer programs)
Language
ISSN
0909-0495
Abstract
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. [ABSTRACT FROM AUTHOR]