An adaptive distributed resampling algorithm with non-proportional allocation

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

  • Omer Demirel - , Max Planck Institute of Molecular Cell Biology and Genetics (Autor:in)
  • Ihor Smal - , Erasmus University Medical Center (Autor:in)
  • Wiro Niessen - , Erasmus University Medical Center (Autor:in)
  • Erik Meijering - , Erasmus University Medical Center (Autor:in)
  • Ivo F. Sbalzarini - , Professur für Wissenschaftliches Rechnen für Systembiologie, Max Planck Institute of Molecular Cell Biology and Genetics, Zentrum für Systembiologie Dresden (CSBD) (Autor:in)

Abstract

The distributed resampling algorithm with non-proportional allocation (RNA) [1] is key to implementing particle filtering applications on parallel computer systems. We extend the original work by Bolić et al. by introducing an adaptive RNA (ARNA) algorithm, improving RNA by dynamically adjusting the particle-exchange ratio and randomizing the process ring topology. This improves the runtime performance of ARNA by about 9% over RNA with 10% particle exchange. ARNA also significantly improves the speed at which information is shared between processing elements, leading to about 20-fold faster convergence. The ARNA algorithm requires only a few modifications to the original RNA, and is hence easy to implement.

Details

OriginalspracheEnglisch
Titel2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Seiten1635-1639
Seitenumfang5
PublikationsstatusVeröffentlicht - 2014
Peer-Review-StatusJa

Publikationsreihe

ReiheInternational Conference on Acoustics, Speech, and Signal Processing (ICASSP)
ISSN1520-6149

Konferenz

Titel2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
Dauer4 - 9 Mai 2014
StadtFlorence
LandItalien

Externe IDs

ORCID /0000-0003-4414-4340/work/159608276

Schlagworte

Schlagwörter

  • Distributed resampling, image processing, parallel computing, particle filter, tracking