Rapid earthquake detection through GPU-Based template matching

Dawei Mu, En Jui Lee, Po Chen

研究成果: Article同行評審

24 引文 斯高帕斯(Scopus)

摘要

The template-matching algorithm (TMA) has been widely adopted for improving the reliability of earthquake detection. The TMA is based on calculating the normalized cross-correlation coefficient (NCC) between a collection of selected template waveforms and the continuous waveform recordings of seismic instruments. In realistic applications, the computational cost of the TMA is much higher than that of traditional techniques. In this study, we provide an analysis of the TMA and show how the GPU architecture provides an almost ideal environment for accelerating the TMA and NCC-based pattern recognition algorithms in general. So far, our best-performing GPU code has achieved a speedup factor of more than 800 with respect to a common sequential CPU code. We demonstrate the performance of our GPU code using seismic waveform recordings from the ML 6.6 Meinong earthquake sequence in Taiwan.

原文English
頁(從 - 到)305-314
頁數10
期刊Computers and Geosciences
109
DOIs
出版狀態Published - 2017 12月

All Science Journal Classification (ASJC) codes

  • 資訊系統
  • 地球科學電腦

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