DarwinGame: Playing Tournaments for Tuning Applications in Noisy Cloud Environments
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3669940.3707259.pdf
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3.29 MB
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Adobe PDF
Checksum (MD5)
958a9cb62720433e1c94ff4373966ae3
Author(s)
Basu Roy, Rohan
Gadepally, Vijay
Tiwari, Devesh
Date Issued
February 3, 2025
Publisher
ACM|Proceedings of the 30th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 1
Citation
Rohan Basu Roy, Vijay Gadepally, and Devesh Tiwari. 2025. DarwinGame: Playing Tournaments for Tuning Applications in Noisy Cloud Environments. In Proceedings of the 30th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 1 (ASPLOS '25). Association for Computing Machinery, New York, NY, USA, 264–279.
Version
Final published version
Abstract
This work introduces a new subarea of performance tuning -- performance tuning in a shared interference-prone computing environment. We demonstrate that existing tuners are significantly suboptimal by design because of their inability to account for interference during tuning. Our solution, DarwinGame, employs a tournament-based design to systematically compare application executions with different tunable parameter configurations, enabling it to identify the relative performance of different tunable parameter configurations in a noisy environment. Compared to existing solutions, DarwinGame achieves more than 27% reduction in execution time, with less than 0.5% performance variability. DarwinGame is the first performance tuner that will help developers tune their applications in shared, interference-prone, cloud environments.
MIT Department
Lincoln Laboratory
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Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3669940.3707259
