A performance and energy analysis of I/O management approaches for exascale systems

The advent of fast, unprecedentedly scalable, yet energy-hungry exascale supercomputers poses a major challenge consisting in sustaining a high performance per watt ratio. While much recent work has explored new approaches to I/O management, aiming to reduce the I/O performance bottleneck exhibited by HPC applications (and hence to improve application performance), there is comparatively little work investigating the impact of I/O management approaches on energy consumption.

In this work, we explore how much energy a supercomputer consumes while running scientific simulations when adopting various I/O management approaches. We closely examine three radically different I/O schemes including time partitioning, dedicated cores, and dedicated nodes. We implement the three approaches within the Damaris I/O middleware and perform extensive experiments with one of the target HPC applications of the Blue Waters sustained-petaflop supercomputer project: the CM1 atmospheric model. Our experimental results obtained on the French Grid'5000 platform highlight the differences between these three approaches and illustrate in which way various configurations of the application and of the system can impact performance and energy consumption.