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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.17922 |
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| _version_ | 1866911280566108160 |
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| author | Krahn, Robert Mädler, Josia Seidl, Christoph Fetzer, Christof |
| author_facet | Krahn, Robert Mädler, Josia Seidl, Christoph Fetzer, Christof |
| contents | Modern software systems are executed on a runtime stack with layers (virtualization, storage, trusted execution, etc.) each incurring an execution and/or monetary cost, which may be mitigated by finding suitable parameter configurations. While specialized parameter tuners exist, they are tied to a particular domain or use case, fixed in type and number of optimization goals, or focused on a specific layer or technology. These limitations pose significant adoption hurdles for specialized and innovative ventures (SIVs) that address a variety of domains and use cases, operate under strict cost-performance constraints requiring tradeoffs, and rely on self-hosted servers with custom technology stacks while having little data or expertise to set up and operate specialized tuners. In this paper, we present Groot - a general-purpose configuration tuner designed to a) be explicitly agnostic of a particular domain or use case, b) balance multiple potentially competing optimization goals, c) support different custom technology setups, and d) make minimal assumptions about parameter types, ranges, or suitable values. Our evaluation on both real-world use cases and benchmarks shows that Groot reliably improves performance and reduces resource consumption in scenarios representative for SIVs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_17922 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | GROOT: General-Purpose Automatic Parameter Tuning Across Layers, Domains, and Use Cases Krahn, Robert Mädler, Josia Seidl, Christoph Fetzer, Christof Performance Modern software systems are executed on a runtime stack with layers (virtualization, storage, trusted execution, etc.) each incurring an execution and/or monetary cost, which may be mitigated by finding suitable parameter configurations. While specialized parameter tuners exist, they are tied to a particular domain or use case, fixed in type and number of optimization goals, or focused on a specific layer or technology. These limitations pose significant adoption hurdles for specialized and innovative ventures (SIVs) that address a variety of domains and use cases, operate under strict cost-performance constraints requiring tradeoffs, and rely on self-hosted servers with custom technology stacks while having little data or expertise to set up and operate specialized tuners. In this paper, we present Groot - a general-purpose configuration tuner designed to a) be explicitly agnostic of a particular domain or use case, b) balance multiple potentially competing optimization goals, c) support different custom technology setups, and d) make minimal assumptions about parameter types, ranges, or suitable values. Our evaluation on both real-world use cases and benchmarks shows that Groot reliably improves performance and reduces resource consumption in scenarios representative for SIVs. |
| title | GROOT: General-Purpose Automatic Parameter Tuning Across Layers, Domains, and Use Cases |
| topic | Performance |
| url | https://arxiv.org/abs/2511.17922 |