A Distributed and Self-Calibrating Model-Predictive Controller for Energy and Thermal Management of High-Performance Multicores

Provided by: edaa
Topic: Hardware
Format: PDF
High-end multicore processors are characterized by high power density with significant spatial and temporal variability. This leads to power and temperature hot-spots, which may cause non-uniform ageing and accelerated chip failure. These critical issues can be tackled on-line by closed-loop thermal and reliability management policies. Model Predictive Controllers (MPC) outperform classic feedback controllers since they are capable of minimizing a cost function while enforcing safe working temperature. Unfortunately basic MPC controllers rely on a-priori knowledge of multicore thermal model and their complexity exponentially grows with the number of controlled cores.

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