Title :
A Single Instruction Multiple Data Particle Filter
Author :
Maskell, Simon ; Alun-Jones, Ben ; Macleod, Malcolm
Author_Institution :
QinetiQ, St Andrews Road, Malvern, UK. s.maskell@signal.qinetiq.com
Abstract :
Particle filters are often claimed to be readily parallelisable. However, the resampling step is non-trivial to implement in a fine-grained parallel architecture. While approaches have been proposed that modify the particle filter to be amenable to such implementation, this paper´s novelty lies in its description of a Single Instruction Multiple Data (SIMD) implementation of a particle filter that uses N processors to process N particles. The resulting algorithm has a time complexity of O((log N)2) when performing resampling using N processors. The algorithm has been implemented using C for Graphics (CG), a language that enables the heavily pipelined architecture of modern graphics cards to be used to imitate a SIMD processor. Initial results are presented.
Keywords :
Character generation; Filtering algorithms; Graphics; Parallel architectures; Particle filters; Prototypes; State estimation; Uncertainty;
Conference_Titel :
Nonlinear Statistical Signal Processing Workshop, 2006 IEEE
Conference_Location :
Cambridge, UK
Print_ISBN :
978-1-4244-0581-7
Electronic_ISBN :
978-1-4244-0581-7
DOI :
10.1109/NSSPW.2006.4378818