On The Performance of Prefix-Sum Parallel Kalman Filters and Smoothers on GPUs
Computation
2025-11-14 v1 Distributed, Parallel, and Cluster Computing
Dynamical Systems
Abstract
This paper presents an experimental evaluation of parallel-in-time Kalman filters and smoothers using graphics processing units (GPUs). In particular, the paper evaluates different all-prefix-sum algorithms, that is, parallel scan algorithms for temporal parallelization of Kalman filters and smoothers in two ways: by calculating the required number of operations via simulation, and by measuring the actual run time of the algorithms on real GPU hardware. In addition, a novel parallel-in-time two-filter smoother is proposed and experimentally evaluated. Julia code for Metal and CUDA implementations of all the algorithms is made publicly available.
Cite
@article{arxiv.2511.10363,
title = {On The Performance of Prefix-Sum Parallel Kalman Filters and Smoothers on GPUs},
author = {Simo Särkkä and Ángel F. García-Fernández},
journal= {arXiv preprint arXiv:2511.10363},
year = {2025}
}