On The Performance of Prefix-Sum Parallel Kalman Filters and Smoothers on GPUs
Simo Särkkä and Ángel F. García-Fernández
本文介绍了使用图形处理单元(GPU)对实时卡曼滤波器和平滑器进行实验评估。 特别是,本文评估了不同的全前缀算法,即通过两种方式对卡尔曼滤波器和平滑器进行时间并行化的并行扫描算法:通过模拟计算所需的操作次数,以及通过测量真实GPU硬件上算法的实际运行时间。 此外,还提出了一种新的并行双过滤器平滑器,并对其进行实验评估。 所有算法的Metal和CUDA实现的Julia代码都是公开的。
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-...