Towards Fine-grained Dynamic Tuning of HPC Applications on Modern Multi-core Architectures

Research output: Contribution to conferencesPaperContributedpeer-review

Contributors

Abstract

There is a consensus that exascale systems should operate within a power envelope of 20MW. Consequently, energy conservation is still considered as the most crucial constraint if such systems are to be realized. So far, most research on this topic focused on strategies such as power capping and dynamic power management. Although these approaches can reduce power consumption, we believe that they might not be sufficient to reach the exascale energy-efficiency goals. Hence, we aim to adopt techniques from embedded systems, where energy-efficiency has always been the fundamental objective. A successful energy-saving technique used in embedded systems is to integrate fine-grained autotuning with dynamic voltage and frequency scaling. In this paper, we apply a similar technique to a real-world HPC application. Our experimental results on a HPC cluster indicate that such an approach saves up to 20% of energy compared to the baseline configuration, with negligible performance loss.

Details

Original languageEnglish
Pages1-12
Number of pages12
Publication statusPublished - 2017
Peer-reviewedYes

External IDs

ORCID /0000-0002-8491-770X/work/141543280
ORCID /0009-0003-0666-4166/work/151475572

Keywords

Sustainable Development Goals

Keywords

  • autotuning, dynamic tuning, energy-efficiency, dynamic voltage and frequency scaling, high performance computing