Thermal modeling and optimal allocation of avionics safety-critical tasks on heterogeneous MPSoCs

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, as required in ARINC 653 standard, while minimizing the MPSoC temperature. To achieve that, we formulate a new optimization problem, we derive its NP-hardness, and we identify its subproblem solvable in polynomial time. Furthermore, 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 °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. • Optimal thermal-aware task allocation with ARINC-653 temporal isolation windows. • Interesting relation between power model fidelity and optimization method performance. • Validation by extensive experiments on three physical hardware platforms. • Measured data and source code of proposed optimization methods is publicly available.