Time series analysis (TSA) comprises methods for extracting information in domains as
diverse as medicine, seismology, speech recognition and economics. Matrix Profile (MP) is …

Time series analysis is an important research topic and a key step in monitoring and
predicting events in many fields. Recently, the Matrix Profile method, and particularly two of …

In this work, we study the problem of efficiently executing a state-of-the-art time series
algorithm class–SCAMP–on a heterogeneous platform comprised of CPU+ High …

The mining of multi-dimensional time series is a crucial step in gaining insights into data
obtained from physical systems and from monitoring infrastructures. A widely accepted …

Time series analysis is an important research topic and a key step in monitoring and
predicting events in many fields. Recently, the Matrix Profile method, and particularly two of …

In recent years, approaches that seek to extract valuable information from large datasets
have become particularly relevant in today's society. In this category, we can highlight those …

One of the most time-consuming kernels of an epileptic seizure detection app is the
computation of the Dynamic Time Warping (DTW) Distance Matrix. This kernel is a good …

In the last few years, the heterogeneous architectures have become dominant in each part of
the computing industry: from heterogeneous GPU accelerators joining multi-core CPUs …

Time series analysis (TSA) comprises methods for extracting information in domains as
diverse as medicine, seismology, speech recognition and economics. Matrix Profile (MP) is …

By continuous advancements in several fields of science and technology during the last
decades, data mining and machine learning tasks have gained noticeable interest. The goal …