Uphill resampling for particle filter and its implementation on graphics processing unit

Date

2023-02-01

Author

Dülger, Özcan
Oğuztüzün, Mehmet Halit S.
Demirekler, Mübeccel

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

109
views

0
downloads

We introduce a new resampling method, named Uphill, that is free from numerical instability and suitable for parallel implementation on graphics processing unit (GPU). Common resampling algorithms such as Systematic suffer from numerical instability when single precision floating point numbers are used. This is due to cumulative summation over the weights of particles when the weights differ widely or the number of particles is large. The Metropolis and Rejection resampling algorithms do not suffer from numerical instability as they only calculate the ratios of weights pairwise rather than perform collective operations over the weights. They are more suitable for the GPU implementation of the particle filter. However, they undergo non-coalesced global memory access patterns which cause their speed deteriorate rapidly as the number of particles gets large. Uphill also does not suffer from numerical instability but, experiences the same non-coalesced global memory access problem with Metropolis and Rejection. We introduce its faster version named Uphill-Fast which eliminates this problem. We make comparisons of Uphill and Uphill-Fast with the Systematic, Metropolis, Metropolis-C2 and Rejection resampling methods with respect to quality and speed. We also compare them on a highly non-linear system. Uphill-Fast runs faster and attains similar quality, in terms of RMSE, in comparison with Metropolis and Rejection when the number of particles is very large. Uphill-Fast runs with roughly same speed as Metropolis-C2 with better variance and MSE when the number of particles is very large.

Subject Keywords

Graphics processing unit, Non-coalesced global memory access problem, Numerical instability problem, Particle filter, Uphill resampling, Uphill-Fast resampling

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85146054076&origin=inward
https://hdl.handle.net/11511/102459

Journal

Parallel Computing

DOI

https://doi.org/10.1016/j.parco.2022.102994

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

Parallel resampling methods for particle filters on graphics processing unit Dülger, Özcan; Oğuztüzün, Mehmet Halit S.; Department of Computer Engineering (2017) This thesis addresses the implementation of the resampling stage of the particle filter on graphics processing unit (GPU). Some of the well-known sequential resampling methods are the Multinomial, Stratified and Systematic resampling. They have dependency in their loop structure which impedes their parallel implementation. Although such impediments were overcome on their GPU implementation, these algorithms suffer from numerical instability due to the accumulation of rounding errors when single precision is...
Acceleration of direct volume rendering with programmable graphics hardware Yalim Keles, Hacer; Es, Alphan; İşler, Veysi (Springer Science and Business Media LLC, 2007-01-01) We propose a method to accelerate direct volume rendering using programmable graphics hardware (GPU). In the method, texture slices are grouped together to form a texture slab. Rendering non-empty slabs from front to back viewing order generates the resultant image. Considering each pixel of the image as a ray, slab silhouette maps (SSMs) are used to skip empty spaces along the ray direction per pixel basis. Additionally, SSMs contain terminated ray information. The method relies on hardware z-occlusion cul...
Accelerated regular grid traversals using extended anisotropic chessboard distance fields on a parallel stream processor Es, Alphan; İşler, Veysi (Elsevier BV, 2007-11-01) Modern graphics processing units (GPUs) are an implementation of parallel stream processors. In recent years, there have been a few studies on mapping ray tracing to the GPU. Since graphics processors are not designed to process complex data structures, it is crucial to explore data structures and algorithms for efficient stream processing. In particular ray traversal is one of the major bottlenecks in ray tracing and direct volume rendering methods. In this work we focus on the efficient regular grid based...
Memory Coalescing Implementation of Metropolis Resampling on Graphics Processing Unit Dülger, Özcan; Oğuztüzün, Mehmet Halit S.; DEMİREKLER, MÜBECCEL (Springer Science and Business Media LLC, 2018-03-01) Owing to many cores in its architecture, graphics processing unit (GPU) offers promise for parallel execution of the particle filter. A stage of the particle filter that is particularly challenging to parallelize is resampling. There are parallel resampling algorithms in the literature such as Metropolis resampling, which does not require a collective operation such as cumulative sum over weights and does not suffer from numerical instability. However, with large number of particles, Metropolis resampling b...
Massive crowd simulation with parallel processing Yılmaz, Erdal; İşler, Veysi; Department of Information Systems (2010) This thesis analyzes how parallel processing with Graphics Processing Unit (GPU) could be used for massive crowd simulation, not only in terms of rendering but also the computational power that is required for realistic simulation. The extreme population in massive crowd simulation introduces an extra computational load, which is quite difficult to meet by using Central Processing Unit (CPU) resources only. The thesis shows the specific methods and approaches that maximize the throughput of GPU parallel com...

Citation Formats

Ö. Dülger, M. H. S. Oğuztüzün, and M. Demirekler, “Uphill resampling for particle filter and its implementation on graphics processing unit,” Parallel Computing, vol. 115, pp. 0–0, 2023, Accessed: 00, 2023. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85146054076&origin=inward.