An Embedded Programmable Processor for Compressive Sensing Applications

Mehdi Safarpour, Ilkka Hautala, Olli Silven
2018 2018 IEEE Nordic Circuits and Systems Conference (NORCAS): NORCHIP and International Symposium of System-on-Chip (SoC)  
An application specific programmable processor is designed based on the analysis of a set of greedy recovery Compressive Sensing (CS) algorithms. The solution is flexible and customizable for a wide range of problem dimensions, as well as algorithms. The versatility of the approach is demonstrated by implementing Orthogonal Matching Pursuits, Approximate Messaging Passing and Normalized Iterative Hard Thresholding algorithms, all using a high-level language. Transported Triggered Architecture
more » ... TA) framework is employed for the efficient implementation of macro operations shared by the algorithms. The performance of the CS algorithms on ARM Cortex-A15 and NIOS II processors has also been investigated, and empirical comparisons are presented. The flexible hardware design implemented on an FPGA achieves up to 7.80Ksample/s recovery at a power dissipation of 42μJ/sample and beats both ARM and NIOS in total power consumption.
doi:10.1109/norchip.2018.8573494 dblp:conf/norchip/SafarpourHS18 fatcat:eer6qc4sf5hlnojvzt5f3nomyq