Emergent Mind

Abstract

Supply voltage scaling is one of the most effective techniques to reduce the power consumption of microprocessors. However, technology limitations such as aging and process variability enforce microprocessor designers to apply pessimistic voltage guardbands to guarantee correct operation in the field for any foreseeable workload. This worst-case design practice makes energy efficiency hard to scale with technology evolution. Improving energy-efficiency requires the identification of the chip design margins through time-consuming and comprehensive characterization of its operational limits. Such a characterization of state-of-the-art multi-core CPUs fabricated in aggressive technologies is a multi-parameter process, which requires statistically significant information. In this paper, we present an automated framework to support system-level voltage and frequency scaling characterization of Applied Micro's state-of-the-art ARMv8-based multicore CPUs used in the X-Gene 2 micro-server family. The fully automated framework can provide fine-grained information of the system's state by monitoring any abnormal behavior that may occur during reduced supply voltage conditions. We also propose a new metric to quantify the behavior of a microprocessor when it operates beyond nominal conditions. Our experimental results demonstrate potential uses of the characterization framework to identify the limits of operation for improved energy efficiency.

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