Pricing schemes for energy-efficient HPC systems: Design and exploration

Abstract

Energy efficiency is of paramount importance for the sustainability of HPC systems. Energy consumption limits the peak performance of supercomputers and accounts for a large share of total cost of ownership. Consequently, system owners and final users have started exploring mechanisms to trade off performance for power consumption, for example through frequency and voltage scaling.However, only a limited number of studies have been devoted to explore the economic viability of performance scaling solutions and to devise pricing mechanisms fostering a more energy-conscious usage of resources, without adversely impacting return-of-investment on the HPC facility. We present a parametrized model to analyze the impact of frequency scaling on energy and to assess the potential total cost benefits for the HPC facility and the user. We evaluate four pricing schemes, considering both facility manager and the user perspectives. We then perform a design space exploration considering current and near-future HPC systems and technologies.

The Italian research on HPC key technologies across EuroHPC

“…It saves energy only during MPI synchronization without inducing a timeto-solution increase for applications. Indeed energy-consumption minimization alone can lead to execution time penalties, which reduces capacity and does not always result in a reduction of the total cost of ownership [6]. With COUNTDOWN the energy saving is obtained transparently to the user, without requiring application code modifications or recompilation of the application.…”

Paving the Way Toward Energy-Aware and Automated Datacentre

“…However, HW-based methods operate by exchanging computational power for energy consumption, and this typically implies that the duration of the HPC applications increases. This poses a challenge for the accounting system [12], as in nowadays most supercomputers the price paid by users depends on the duration of their jobs. Hence, alternative means for enforcing power capping have been widely studied.…”

“…While previous Sections focuses on automating the maintenance tasks of the computing infrastructure, not a lot is done in terms of increasing its efficiency. The ExaMon framework enables users to assess the energy consumed by their running job, but let them control the energy consumed by their job could be detrimental to the supercomputing capacity and TCO [12].…”

“…Power states transitions are controlled by hardware policies [23,28], operating system (OS) policies, and with an increasing emphasis in recent years, at user-space by the final users [3,20,21,24] and at execution time [25,30]. However, exploring the EtS (Energy-to-Solution)-TtS (Time-to-Solution) Pareto curve at run-time has a limited potential in the current supercomputing scenario: slowing down applications is often detrimental to the total cost of ownership (TCO) due to the large contribution related to the depreciation cost of the IT equipment [12].…”

COUNTDOWN: a Run-time Library for Performance-Neutral Energy Saving in MPI Applications

“…The main drawback of the works mentioned so far is that they lead to a systematic increase of TTS, which may be acceptable for the user, but it is not easily acceptable by the facility manager since it reduces the data center cost efficiency and TCO [12]. For this reason, there is a trend in the literature towards HPC energy reduction methodologies with negligible or low impact on TTS of the running applications.…”