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TY - CONF AU - Murari, J.F.J. AU - Klementiev, K. ED - Schaa, Volker RW ED - Costa, Isidre ED - Fernández, David ED - Matilla, Ãscar TI - Parallel Execution of Sequential Data Analysis J2 - Proc. of ICALEPCS2017, Barcelona, Spain, 8-13 October 2017 C1 - Barcelona, Spain T2 - International Conference on Accelerator and Large Experimental Control Systems T3 - 16 LA - english AB - The Parallel Execution of Sequential Data Analysis (ParSeq) software has been developed to work on large data sets of thousands spectra of a thousand points each. The main goal of this tool is to perform spectroscopy analysis without delays on the large amount of data that will be generated on Balder beamline at Max IV *. ParSeq was developed using Python and PyQt and can be operated via scripts or graphical user interface (GUI). The pipeline is consisted of nodes and transforms. Each node generally has a common group of components: data manager (also serves as legend), data combiner, metadata viewer, transform dialog, help panel and a plot window (from silx library **) as main element. The transforms connect nodes, applying the respective parameters in the active data. It is also possible to create cross-data linear combinations (e.g. averaging, RMS or PCA) and propagate them downstream. Calculations will be done with parallel execution on GPU. The GUI is very flexible and user-friendly, containing splitters, dock widgets, colormaps and undo/redo options. The features mentioned are missing in other analysis platforms what justifies the creation of ParSeq. PB - JACoW CP - Geneva, Switzerland SP - 1877 EP - 1879 KW - ion KW - GUI KW - GPU KW - data-analysis KW - controls DA - 2018/01 PY - 2018 SN - 978-3-95450-193-9 DO - 10.18429/JACoW-ICALEPCS2017-THPHA186 UR - http://jacow.org/icalepcs2017/papers/thpha186.pdf ER -