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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2509.25090 |
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| _version_ | 1866909814864478208 |
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| author | Roy, Rohan Basu Gadepally, Vijay Tiwari, Devesh |
| author_facet | Roy, Rohan Basu Gadepally, Vijay Tiwari, Devesh |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_25090 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | DarwinGame: Playing Tournaments for Tuning Applications in Noisy Cloud Environments Roy, Rohan Basu Gadepally, Vijay Tiwari, Devesh Performance 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. |
| title | DarwinGame: Playing Tournaments for Tuning Applications in Noisy Cloud Environments |
| topic | Performance |
| url | https://arxiv.org/abs/2509.25090 |