Going Green for Less Green: Optimizing the Cost of Reducing Cloud Carbon Emissions

ASPLOS '24: Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems April 27-May 1, 2024, La Jolla, CA, USA

書目詳細資料
Main Authors: Hanafy, Walid A., Liang, Qianlin, Bashir, Noman, Souza, Abel, Irwin, David, Shenoy, Prashant
其他作者: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
格式: Article
語言:English
出版: ACM 2024
在線閱讀:https://hdl.handle.net/1721.1/154384
_version_ 1826210422209904640
author Hanafy, Walid A.
Liang, Qianlin
Bashir, Noman
Souza, Abel
Irwin, David
Shenoy, Prashant
author2 Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
author_facet Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Hanafy, Walid A.
Liang, Qianlin
Bashir, Noman
Souza, Abel
Irwin, David
Shenoy, Prashant
author_sort Hanafy, Walid A.
collection MIT
description ASPLOS '24: Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems April 27-May 1, 2024, La Jolla, CA, USA
first_indexed 2024-09-23T14:49:13Z
format Article
id mit-1721.1/154384
institution Massachusetts Institute of Technology
language English
last_indexed 2025-02-19T04:24:01Z
publishDate 2024
publisher ACM
record_format dspace
spelling mit-1721.1/1543842025-01-02T05:05:54Z Going Green for Less Green: Optimizing the Cost of Reducing Cloud Carbon Emissions Hanafy, Walid A. Liang, Qianlin Bashir, Noman Souza, Abel Irwin, David Shenoy, Prashant Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory ASPLOS '24: Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems April 27-May 1, 2024, La Jolla, CA, USA The continued exponential growth of cloud datacenter capacity has increased awareness of the carbon emissions when executing large compute-intensive workloads. To reduce carbon emissions, cloud users often temporally shift their batch workloads to periods with low carbon intensity. While such time shifting can increase job completion times due to their delayed execution, the cost savings from cloud purchase options, such as reserved instances, also decrease when users operate in a carbon-aware manner. This happens because carbon-aware adjustments change the demand pattern by periodically leaving resources idle, which creates a trade-off between carbon emissions and cost. In this paper, we present GAIA, a carbon-aware scheduler that enables users to address the three-way trade-off between carbon, performance, and cost in cloud-based batch schedulers. Our results quantify the carbon-performance-cost trade-off in cloud platforms and show that compared to existing carbon-aware scheduling policies, our proposed policies can double the amount of carbon savings per percentage increase in cost, while decreasing the performance overhead by 26%. 2024-05-02T19:33:51Z 2024-05-02T19:33:51Z 2024-04-27 2024-05-01T07:46:00Z Article http://purl.org/eprint/type/JournalArticle 979-8-4007-0386-7 https://hdl.handle.net/1721.1/154384 Hanafy, Walid A., Liang, Qianlin, Bashir, Noman, Souza, Abel, Irwin, David et al. 2024. "Going Green for Less Green: Optimizing the Cost of Reducing Cloud Carbon Emissions." PUBLISHER_CC en 10.1145/3620666.3651374 Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ The author(s) application/pdf ACM Association for Computing Machinery
spellingShingle Hanafy, Walid A.
Liang, Qianlin
Bashir, Noman
Souza, Abel
Irwin, David
Shenoy, Prashant
Going Green for Less Green: Optimizing the Cost of Reducing Cloud Carbon Emissions
title Going Green for Less Green: Optimizing the Cost of Reducing Cloud Carbon Emissions
title_full Going Green for Less Green: Optimizing the Cost of Reducing Cloud Carbon Emissions
title_fullStr Going Green for Less Green: Optimizing the Cost of Reducing Cloud Carbon Emissions
title_full_unstemmed Going Green for Less Green: Optimizing the Cost of Reducing Cloud Carbon Emissions
title_short Going Green for Less Green: Optimizing the Cost of Reducing Cloud Carbon Emissions
title_sort going green for less green optimizing the cost of reducing cloud carbon emissions
url https://hdl.handle.net/1721.1/154384
work_keys_str_mv AT hanafywalida goinggreenforlessgreenoptimizingthecostofreducingcloudcarbonemissions
AT liangqianlin goinggreenforlessgreenoptimizingthecostofreducingcloudcarbonemissions
AT bashirnoman goinggreenforlessgreenoptimizingthecostofreducingcloudcarbonemissions
AT souzaabel goinggreenforlessgreenoptimizingthecostofreducingcloudcarbonemissions
AT irwindavid goinggreenforlessgreenoptimizingthecostofreducingcloudcarbonemissions
AT shenoyprashant goinggreenforlessgreenoptimizingthecostofreducingcloudcarbonemissions