Parallel high-performance computing of Bayes estimation for signal processing and metrology
Garcia E, Zschiegner N, Hausotte T (2013)
Publication Type: Conference contribution
Publication year: 2013
Publisher: IEEE SERVICE CENTER, 445 HOES LANE, PO BOX 1331, PISCATAWAY, NJ 08855-1331 USA
Pages Range: 212-218
Conference Proceedings Title: Proceedings of the IEEE International Conference on Computing, Management & Telecommunications
Event location: Ho Chi Minh City, Vietnam
Abstract
The Bayesian theorem is the most used instrument for stochastic inferencing in nonlinear dynamic systems. The algorithmic implementations of the recursive Bayesian estimation for arbitrary systems are the particle filters (PFs). They are sampling-based sequential Monte-Carlo methods, which generate a set of samples to compute an approximation of the Bayesian posterior probability density function. Thus, the PF faces the problem of high computational burden, since it converges to the true posterior when number of particles N-P -> infinity. In order to solve these computational problems a highly parallelized C++ library, called Parallel Bayesian Toolbox (PBT), for implementing Bayes filters (BFs) was developed and released as open-source software, for the first time [1]. It features a high level language interface for numerical calculations and very efficient usage of available central processing units (CPUs) and graphics processing units (GPUs). This significantly increases the computational throughput without the need of special hardware such as application-specific integrated circuits (ASICs) or field-programmable gate arrays (FPGAs).
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Related research project(s)
None - None
Datenfusion multisensoriell ausgeführter Koordinatenmessungen (BayesMultiKo)
Jan. 1, 2010 - Aug. 31, 2013
How to cite
APA:
Garcia, E., Zschiegner, N., & Hausotte, T. (2013). Parallel high-performance computing of Bayes estimation for signal processing and metrology. In Proceedings of the IEEE International Conference on Computing, Management & Telecommunications (pp. 212-218). Ho Chi Minh City, Vietnam, VN: IEEE SERVICE CENTER, 445 HOES LANE, PO BOX 1331, PISCATAWAY, NJ 08855-1331 USA.
MLA:
Garcia, Elmar, Nils Zschiegner, and Tino Hausotte. "Parallel high-performance computing of Bayes estimation for signal processing and metrology." Proceedings of the IEEE International Conference on Computing, Management & Telecommunications, Ho Chi Minh City, Vietnam IEEE SERVICE CENTER, 445 HOES LANE, PO BOX 1331, PISCATAWAY, NJ 08855-1331 USA, 2013. 212-218.
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