https://github.com/automaticdai/research-mcs-ap-analysis
Experiment code for the analysis in "HIART-MCS: High Resilience and Approximated Computing Architecture for Imprecise Mixed-Criticality Systems". RTSS 2021
https://github.com/automaticdai/research-mcs-ap-analysis
Last synced: 10 months ago
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Experiment code for the analysis in "HIART-MCS: High Resilience and Approximated Computing Architecture for Imprecise Mixed-Criticality Systems". RTSS 2021
- Host: GitHub
- URL: https://github.com/automaticdai/research-mcs-ap-analysis
- Owner: automaticdai
- Created: 2021-05-17T22:13:06.000Z (about 5 years ago)
- Default Branch: main
- Last Pushed: 2022-05-23T20:58:52.000Z (about 4 years ago)
- Last Synced: 2025-06-30T02:07:23.572Z (12 months ago)
- Language: Python
- Homepage:
- Size: 67.4 KB
- Stars: 1
- Watchers: 1
- Forks: 2
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Analysis of Mixed-Criticality System Approximated Computing (MCS-AP)
## Introduction
This is the code of the schedulability analysis part of our RTSS 2021 paper, "HIART-MCS: High Resilience and Approximated Computing Architecture for Imprecise Mixed-Criticality Systems", by Zhe Jiang, Xiaotian Dai, and Neil Audsley.
## Usage
1. Run the examples and save outputs with `python3 main.py >> data.txt`
2. Plot the results with MATLAB scripts `plot1.m` and `plot2.m` , do point the directory folder to the right `data.txt`
## Citation
To cite this work:
> Zhe Jiang, Xiaotian Dai, Neil Audsley. "HIART-MCS: High Resilience and Approximated Computing Architecture for Imprecise Mixed-Criticality Systems". Real Time Systems Symposium (RTSS). 2021