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Best-Match Time Series Subsequence Search on the Intel Many Integrated Core Architecture

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Advances in Databases and Information Systems (ADBIS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9282))

Abstract

Subsequence similarity search is one of the basic problems of time series data mining. Nowadays Dynamic Time Warping (DTW) is considedered as the best similarity measure. However despite various existing software speedup techniques DTW is still computationally expensive. There are approaches to speed up DTW computation by means of parallel hardware (e.g. GPU and FPGA) but accelerators based on the Intel Many Integrated Core architecture have not been payed attention. The paper presents a parallel algorithm for best-match time series subsequence search based on DTW distance for the Intel Xeon Phi coprocessor. The experimental results on synthetic and real data sets confirm the efficiency of the algorithm.

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Notes

  1. 1.

    One of the coprocessor’s cores is not involved in computations as it is recommended by the Intel Xeon Phi programmer’s manual.

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Acknowledgment

This work was financially supported by the Ministry of education and science of the Russian Federation (“Research and development on priority directions of scientific-technological complex of Russia for 2014–2020” Federal Program, contract No. 14.574.21.0035).

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Authors and Affiliations

  1. South Ural State University, Chelyabinsk, Russia

    Mikhail Zymbler

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  1. Mikhail Zymbler
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Correspondence to Mikhail Zymbler .

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Editors and Affiliations

  1. Poznan University of Technology, Poznán, Poland

    Morzy Tadeusz

  2. INRIA, Montpellier, France

    Patrick Valduriez

  3. Teleport 2, LIAS/ISAE-ENSMA, Poitiers, France

    Ladjel Bellatreche

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Zymbler, M. (2015). Best-Match Time Series Subsequence Search on the Intel Many Integrated Core Architecture. In: Tadeusz, M., Valduriez, P., Bellatreche, L. (eds) Advances in Databases and Information Systems. ADBIS 2015. Lecture Notes in Computer Science(), vol 9282. Springer, Cham. https://doi.org/10.1007/978-3-319-23135-8_19

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  • DOI: https://doi.org/10.1007/978-3-319-23135-8_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23134-1

  • Online ISBN: 978-3-319-23135-8

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