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A Comparison of Serial & Parallel Particle Filters for Time Series Analysis

David Klemish
Departments of Statistical Science & Economics, Duke University
Duke University, 2014

@phdthesis{klemish2014comparison,

   title={A Comparison of Serial & Parallel Particle Filters for Time Series Analysis},

   author={Klemish, David},

   year={2014},

   school={Duke University}

}

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This paper discusses the application of parallel programming techniques to the estimation of hidden Markov models via the use of a particle filter. It highlights how the Thrust parallel programming language can be used to implement a particle filter in parallel. The impact of a parallel particle filter on the running times of three different models is investigated. For particle filters using a large number of particles, Thrust provides a speed-up of five to ten times over a serial C++ implementation, which is less than reported in other research.
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