Publication Details
Analyzing Dynamic Aspects of AxC Systems by Means of Statistical Model Checking
approximate circuit, error, trade-off, relaxed equivalence, verification, timed
automaton, stochastic automaton, modeling, simulation, model checking
Many researchers shown that approximate circuits are able to provide a new
perspective on the development of electronic systems. Mostly, they tried to find
an optimal trade-off between the approximation error and resource savings for
predefined applications. However, they used to concentrate mainly on design
aspects regarding relaxed functional requirements, but neglected aspects like
timing, sequential/asynchronous nature of circuits, uncertainty due to
process/parameter variations, excessively high operating frequencies or low
voltages. This paper aims to take a step ahead by moving towards the verification
of dynamic properties of systems based on approximate circuits, with a focus on
sequential/asynchronous circuits and uncertainty. First, the paper presents our
approach to modeling approximate systems by means of stochastic hybrid timed
automata. Then, it shows the principle/advantage of verifying properties of
modeled systems by the so-called statistical model checking technique. Further,
it presents a framework that takes at its input the model of an accurate system,
its timing and other requirements and expected properties, information about
basic building blocks and acceptable cost/quality trade-off to produce an
approximated system that meets the requirements maximally and satisfies the
properties. Finally, the paper evaluates our approach and outlines future
research perspectives.
@inproceedings{BUT176816,
author="Josef {Strnadel}",
title="Analyzing Dynamic Aspects of AxC Systems by Means of Statistical Model Checking",
booktitle="Proceedings of 2022 25th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS)",
year="2022",
pages="88--93",
publisher="Institute of Electrical and Electronics Engineers",
address="Prague",
doi="10.1109/DDECS54261.2022.9770166",
isbn="978-1-6654-9431-1"
}