Redistribution Networks for Resampling

Description

Resampling is an important building block in core signal processing methods such as particle filters or genetic algorithms. This work describes how to accelerate the redistribution part of resampling, in a parallelized form utilizing a processing network composed of low-complexity nodes with O(log2^2(n)) layers. We furthermore show how to use such networks for block-based processing of input vectors that are larger than the input of the network, allowing to trade-off the best of both worlds: block-based processing with its low area requirements and network-based processing with its high speed. We present simulation results not only showing the performance gains compared to the trivial linear method but also showing that by using the proposed architecture one can achieve processing times on edge devices that recently required high-performance server clusters.

Period	11 Dec 2023
Event title	2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
Event type	Conference
Location	Costa RicaShow on map