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Communication Dans Un Congrès Année : 2015

Application-Agnostic Framework for Improving the Energy Efficiency of Multiple HPC Subsystems

Résumé

The subsystems that compose a HPC platform (e.g. CPU, memory, storage and network) are often designed and configured to deliver exceptional performance to a wide range of workloads. As a result, a large part of the power that these subsystems consume is dissipated as heat even when executing workloads that do not require maximum performance. Attempts to tackle this problem include technologies whereby operating systems and applications can reconfigure subsystems dynamically, such as by using DVFS for CPUs, LPI for network components, and variable disk spinning for HDDs. Most previous work has explored these technologies individually to optimise workload execution and reduce energy consumption. We propose a framework that performs on-line analysis of an HPC system in order to identify application execution patterns without a priori information of their workload. The framework takes advantage of reoccurring patterns to reconfigure multiple subsystems dynamically and reduce overall energy consumption. Performance evaluation was carried out on Grid'5000 considering both traditional HPC benchmarks and real-life applications.
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Dates et versions

hal-01094431 , version 1 (04-05-2023)

Identifiants

Citer

Ghislain Landry Tsafack Chetsa, Laurent Lefevre, Jean-Marc Pierson, Patricia Stolf, Georges da Costa. Application-Agnostic Framework for Improving the Energy Efficiency of Multiple HPC Subsystems. 23rd Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP 2015), Mar 2015, Turku, Finland. ⟨10.1109/PDP.2015.18⟩. ⟨hal-01094431⟩
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