Thermal Modeling and Optimal Allocation of Avionics Safety-critical Tasks on Heterogeneous MPSoCs

TL;DR

This paper presents thermal-aware task allocation techniques for heterogeneous MPSoCs in avionics, optimizing for reduced temperature while considering power models and various optimization methods.

Contribution

It introduces novel thermal-aware allocation approaches using power models and optimization techniques, tailored for safety-critical avionics MPSoC systems.

Findings

Up to 5.5°C temperature reduction achieved.

The ILP-based method outperforms other approaches.

Significant thermal improvements across multiple platforms.

Abstract

Multi-Processor Systems-on-Chip (MPSoC) can deliver high performance needed in many industrial domains, including aerospace. However, their high power consumption, combined with avionics safety standards, brings new thermal management challenges. This paper investigates techniques for offline thermal-aware allocation of periodic tasks on heterogeneous MPSoCs running at a fixed clock frequency, as required in avionics. The goal is to find the assignment of tasks to (i) cores and (ii) temporal isolation windows while minimizing the MPSoC temperature. To achieve that, we propose and analyze three power models, and integrate them within several novel optimization approaches based on heuristics, a black-box optimizer, and Integer Linear Programming (ILP). We perform the experimental evaluation on three popular MPSoC platforms (NXP i.MX8QM MEK, NXP i.MX8QM Ixora, NVIDIA TX2) and observe a difference of up to 5.5{\deg}C among the tested methods (corresponding to a 22% reduction w.r.t. the ambient temperature). We also show that our method, integrating the empirical power model with the ILP, outperforms the other methods on all tested platforms.