Open AccessEnergy-Efficient NoC-Based Systems for Real-Time Multimedia Applications using Approximate Computing
Author(s) -
Wagner Penny,
Daniel Palomino,
Marcelo Porto,
Bruno Zatt
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/ctd.2021.15750
Subject(s) - computer science , scalability , energy consumption , quality of service , workload , efficient energy use , embedded system , real time computing , distributed computing , computer network , engineering , operating system , electrical engineering
This work presents an energy-efficient NoC-based system for real-time multimedia applications employing approximate computing. The proposed video processing system, called SApp-NoC, is efficient in both energy and quality (QoS), employing a scalable NoC architecture composed of processing elements designed to accelerate the HEVC Fractional Motion Estimation (FME). Two solutions are proposed: HSApp-NoC (Heuristc-based SApp-NoC), and MLSApp-NoC (Machine Learning-based SApp-NoC). When compared to a precise solution processing 4K videos at 120 fps, HSApp-NoC and MLSApp-NoC reduce about 48.19% and 31.81% the energy consumption, at small quality reduction of 2.74% and 1.09%, respectively. Furthermore, a set of schedulability analysis is also proposed in order to guarantee the meeting of timing constraints at typical workload scenarios.