MIMO-RLS-LQR Adaptive Governor for Multi-Cluster DVFS

Abstract: This paper introduces a novel control-theoretic adaptive governor for Dynamic Voltage and Frequency Scaling (DVFS) in modern heterogeneous multi-cluster processors. Standard Linux scaling governors, such as schedutil, fundamentally rely on heuristic look-up approaches that struggle to maintain optimal performance-thermal trade-offs under dynamic, highly variable workloads. To resolve this limitation, we present an internally closed loop framework that models multi-cluster frequency domain interaction as a multi-variable problem. The architecture integrates an online Multi-Input Multi-Output Recursive Least Squares (MIMO-RLS) estimator for real-time, non-stationary system identification, combined with a periodic Linear Quadratic Regulator (LQR) optimal control system computed over a six-dimensional state vector. Robust multi-layer safety thresholds are introduced to handle transient instabilities in userspace actuation. Experimental evaluations conducted on Raspberry Pi 5 (Broadcom BCM2712) and Orange Pi 5 Plus (Rockchip RK3588) platforms demonstrate measurable improvements in thermal stabilization (up to 5°C reduction in peak core temperatures) and systemic energy efficiency compared to default kernel behaviors, with acceptable execution time overhead.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-19
DOI
https://doi.org/10.5281/zenodo.20285492
Primary Topic
Parallel Computing and Optimization Techniques
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

MIMO-RLS-LQR Adaptive Governor for Multi-Cluster DVFS

Stanislav Usychenko
Zenodo (CERN European Organization for Nuclear Research)
Parallel Computing and Optimization Techniques
preprint

MIMO-RLS-LQR Adaptive Governor for Multi-Cluster DVFS

Stanislav Usychenko
preprint en

Abstract

Abstract: This paper introduces a novel control-theoretic adaptive governor for Dynamic Voltage and Frequency Scaling (DVFS) in modern heterogeneous multi-cluster processors. Standard Linux scaling governors, such as schedutil, fundamentally rely on heuristic look-up approaches that struggle to maintain optimal performance-thermal trade-offs under dynamic, highly variable workloads. To resolve this limitation, we present an internally closed loop framework that models multi-cluster frequency domain interaction as a multi-variable problem. The architecture integrates an online Multi-Input Multi-Output Recursive Least Squares (MIMO-RLS) estimator for real-time, non-stationary system identification, combined with a periodic Linear Quadratic Regulator (LQR) optimal control system computed over a six-dimensional state vector. Robust multi-layer safety thresholds are introduced to handle transient instabilities in userspace actuation. Experimental evaluations conducted on Raspberry Pi 5 (Broadcom BCM2712) and Orange Pi 5 Plus (Rockchip RK3588) platforms demonstrate measurable improvements in thermal stabilization (up to 5°C reduction in peak core temperatures) and systemic energy efficiency compared to default kernel behaviors, with acceptable execution time overhead.

Zenodo (CERN European Organization for Nuclear Research)
Affordable and clean energy
Parallel Computing and Optimization Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.