Accurate Energy Modelling on the Cortex-M0 Processor for Profiling and Static Analysis

01/30/2023
by   Kris Nikov, et al.
0

Energy modelling can enable energy-aware software development and assist the developer in meeting an application's energy budget. Although many energy models for embedded processors exist, most do not account for processor-specific configurations, neither are they suitable for static energy consumption estimation. This paper introduces a set of comprehensive energy models for Arm's Cortex-M0 processor, ready to support energy-aware development of edge computing applications using either profiling- or static-analysis-based energy consumption estimation. We use a commercially representative physical platform together with a custom modified Instruction Set Simulator to obtain the physical data and system state markers used to generate the models. The models account for different processor configurations which all have a significant impact on the execution time and energy consumption of edge computing applications. Unlike existing works, which target a very limited set of applications, all developed models are generated and validated using a very wide range of benchmarks from a variety of emerging IoT application areas, including machine learning and have a prediction error of less than 5

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/02/2021

A Comprehensive and Accurate Energy Model for Arm's Cortex-M0 Processor

Energy modeling can enable energy-aware software development and assist ...
research
05/24/2023

EnergyAnalyzer: Using Static WCET Analysis Techniques to Estimate the Energy Consumption of Embedded Applications

This paper presents EnergyAnalyzer, a code-level static analysis tool fo...
research
07/05/2019

Energy of Computing on Multicore CPUs: Predictive Models and Energy Conservation Law

Energy is now a first-class design constraint along with performance in ...
research
08/25/2016

Energy Transparency for Deeply Embedded Programs

Energy transparency is a concept that makes a program's energy consumpti...
research
05/06/2020

AVAC: A Machine Learning based Adaptive RRAM Variability-Aware Controller for Edge Devices

Recently, the Edge Computing paradigm has gained significant popularity ...
research
08/31/2023

An Energy-Aware Approach to Design Self-Adaptive AI-based Applications on the Edge

The advent of edge devices dedicated to machine learning tasks enabled t...
research
11/09/2020

von Neumann's missing "Second Draft": what it should contain

Computing science is based on a computing paradigm that is not valid any...

Please sign up or login with your details

Forgot password? Click here to reset