  The race towards performance increase and computing power has led to chips
with heterogeneous and complex designs, integrating an ever-growing number of
cores on the same monolithic chip or chiplet silicon die. Higher integration
density, compounded with the slowdown of technology-driven power reduction,
implies that power and thermal management become increasingly relevant.
Unfortunately, existing research lacks a detailed analysis and modeling of
thermal, power, and electrical coupling effects and how they have to be jointly
considered to perform dynamic control of complex and heterogeneous
Multi-Processor System on Chips (MPSoCs). To close the gap, in this work, we
first provide a detailed thermal and power model targeting a modern High
Performance Computing (HPC) MPSoC. We consider real-world coupling effects such
as actuators' non-idealities and the exponential relation between the
dissipated power, the temperature state, and the voltage level in a single
processing element. We analyze how these factors affect the control algorithm
behavior and the type of challenges that they pose. Based on the analysis, we
propose a thermal capping strategy inspired by Fuzzy control theory to replace
the state-of-the-art PID controller, as well as a root-finding iterative method
to optimally choose the shared voltage value among cores grouped in the same
voltage domain. We evaluate the proposed controller with model-in-the-loop and
hardware-in-the-loop co-simulations. We show an improvement over
state-of-the-art methods of up to 5x the maximum exceeded temperature while
providing an average of 3.56% faster application execution runtime across all
the evaluation scenarios.
