Quantifying the impact of variability on the energy efficiency for a next-generation ultra-green supercomputer

Abstract

Supercomputers, nowadays, aggregate a large number of nodes sharing the same nominal HW components (eg. processors and GPGPUS). In real-life machines, the chips populating each node are subject to a wide range of variability sources, related to performance and temperature operating points (i.e. ACPI p-states) as well as process variations and die binning. Eurora is a fully operational supercomputer prototype that topped July 2013 Green500 and it represents a unique 'living lab' for next-generation ultra-green supercomputers. In this paper we evaluate and quantify the impact of variability on Eurora's energy-performance tradeoffs under a wide range of workload intensity.