High-resolution online power monitoring for modern microprocessors

The power consumption of computing systems is nowadays a major design constraint that affects performance and reliability. To co-optimize these aspects, fine-grained adaptation techniques at runtime are of growing importance. However, to use these tools efficiently, fine-grained information about the power consumption of various on-chip components at runtime is required. Therefore, here we propose a novel software-implemented high-resolution (spatial and temporal) power monitoring approach that relies on micro-models to estimate the power consumption of all microarchitectural components inside a processor core. Combined with a self-calibration technique that uses an available on-chip power sensor, our power estimation approach can achieve an accuracy of more than 99 % and provides deep insights about the power dissipation inside a processor core during workload execution.