The growth of cloud services leads to more and more data centers that are increasingly larger and consume considerable amounts of power. To increase energy efficiency, both the actual server equipment and the software must become more energy efficient. Software has a major impact on hardware utilization levels, and subsequently, the energy efficiency. While energy efficiency is often seen as identical to performance, we argue that this may not be necessarily the case. A sizable amount of energy could be saved, increasing energy efficiency by leveraging compiler optimizations but at the same time impacting performance and power consumption over time. We analyze the SPEC CPU 2017 benchmark suite with 43 benchmarks from different domains, including integer and floating-point heavy computations on a state-of-the-art server system for cloud applications. Our results show that power consumption displays more stable behavior if less compiler optimizations are used and also confirmed that performance and energy efficiency are different optimizations goals. Additionally, compiler optimizations possibly could be used to enable power capping on a software level and care must be taken when selecting such optimizations.
%0 Conference Paper
%1 9302787
%A Schmitt, Norbert
%A Bucek, James
%A Beckett, John
%A Cragin, Aaron
%A Lange, Klaus-Dieter
%A Kounev, Samuel
%B 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC)
%D 2020
%K descartes power power-energy_efficient_computing myown
%P 292-301
%T Performance, Power, and Energy-Efficiency Impact Analysis of Compiler Optimizations on the SPEC CPU 2017 Benchmark Suite
%U https://ieeexplore.ieee.org/document/9302787/
%X The growth of cloud services leads to more and more data centers that are increasingly larger and consume considerable amounts of power. To increase energy efficiency, both the actual server equipment and the software must become more energy efficient. Software has a major impact on hardware utilization levels, and subsequently, the energy efficiency. While energy efficiency is often seen as identical to performance, we argue that this may not be necessarily the case. A sizable amount of energy could be saved, increasing energy efficiency by leveraging compiler optimizations but at the same time impacting performance and power consumption over time. We analyze the SPEC CPU 2017 benchmark suite with 43 benchmarks from different domains, including integer and floating-point heavy computations on a state-of-the-art server system for cloud applications. Our results show that power consumption displays more stable behavior if less compiler optimizations are used and also confirmed that performance and energy efficiency are different optimizations goals. Additionally, compiler optimizations possibly could be used to enable power capping on a software level and care must be taken when selecting such optimizations.
@inproceedings{9302787,
abstract = {The growth of cloud services leads to more and more data centers that are increasingly larger and consume considerable amounts of power. To increase energy efficiency, both the actual server equipment and the software must become more energy efficient. Software has a major impact on hardware utilization levels, and subsequently, the energy efficiency. While energy efficiency is often seen as identical to performance, we argue that this may not be necessarily the case. A sizable amount of energy could be saved, increasing energy efficiency by leveraging compiler optimizations but at the same time impacting performance and power consumption over time. We analyze the SPEC CPU 2017 benchmark suite with 43 benchmarks from different domains, including integer and floating-point heavy computations on a state-of-the-art server system for cloud applications. Our results show that power consumption displays more stable behavior if less compiler optimizations are used and also confirmed that performance and energy efficiency are different optimizations goals. Additionally, compiler optimizations possibly could be used to enable power capping on a software level and care must be taken when selecting such optimizations.},
added-at = {2022-09-21T01:05:36.000+0200},
author = {Schmitt, Norbert and Bucek, James and Beckett, John and Cragin, Aaron and Lange, Klaus-Dieter and Kounev, Samuel},
biburl = {https://www.bibsonomy.org/bibtex/22fdca90dfd17e1f037b3d31617ea1d33/samuel.kounev},
booktitle = {2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC)},
interhash = {e169120838d85efdd353d8763ea9e42c},
intrahash = {2fdca90dfd17e1f037b3d31617ea1d33},
keywords = {descartes power power-energy_efficient_computing myown},
month = dec,
pages = {292-301},
timestamp = {2022-09-21T01:05:36.000+0200},
title = {Performance, Power, and Energy-Efficiency Impact Analysis of Compiler Optimizations on the SPEC CPU 2017 Benchmark Suite},
url = {https://ieeexplore.ieee.org/document/9302787/},
year = 2020
}