Power Capping techniques are used to restrict power consumption of computer systems to a thermally safe limit. Current many-core systems employ dynamic voltage and frequency scaling (DVFS), power gating (PG) and scheduling methods as actuators for power capping. These knobs arc oriented towards power actuation, while the need for performance and energy savings are increasing in the dark silicon era. To address this, we propose approximation (APPX) as another knob for close-looped power management, lending performance and energy efficiency to existing power capping techniques. We use approximation in a pro-active way for long-term performance-energy objectives, complementing the short-term reactive power objectives. We implement an approximation-enabled power management framework, APPEND, that dynamically chooses an application with appropriate level of approximation from a set of variable accuracy implementations. Subject to the system dynamics, our power manager chooses an effective combination of knobs - APPX, DVFS and PG, in a hierarchical way to ensure power capping with performance and energy gains. Our proposed approach yields 1.5× higher throughput, improved latency upto 5×, better performance per energy and dark silicon mitigation compared to state-of-the-art power management techniques over a set of applications ranging from high to no error resilience.
['Anil Kanduri', 'Mohammad Hashem Haghbayan', 'Amir-Mohammad Rahmani', 'Pasi Liljeberg', 'Axel Jantsch', 'Nikil Dutt', 'Hannu Tenhunen']
Approximation knob: power capping meets energy efficiency