Speaker
Tomáš Martinovič
(IT4Innovations, VŠB - Technical University of Ostrava)
Description
Recurrence quantitative analysis (RQA) is a quantification of structures in the recurrence plots. It is used to study the dynamical properties of the systems represented by the time series data. Although RQA is a powerful tool in time series analysis, it has an exponential computation complexity. Therefore, it is difficult to use RQA to analyze very long time series. This work focuses on the scalable parallel computation of the RQA. This algorithm greatly reduces spatial complexity of existing methods and allows parallelization with a small amount of communication. Scalability of the MPI (Message Passing Interface) implementation was tested and it is shown it scales very well.
Primary author
Tomáš Martinovič
(IT4Innovations, VŠB - Technical University of Ostrava)
Co-author
Mr
Georg Zitzlsberger
(IT4Innovations, VŠB - Technical University of Ostrava)
