Profiling Multi-Level Operator Costs for Bottleneck Diagnosis in High-Speed Data Planes
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916895968460800 |
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| author | Ren, Zhiyuan Liu, Yutao Cheng, Wenchi Yang, Kun |
| author_facet | Ren, Zhiyuan Liu, Yutao Cheng, Wenchi Yang, Kun |
| contents | This paper proposes a saturation throughput delta-based methodology to precisely measure operator costs in high-speed data planes without intrusive instrumentation. The approach captures non-linear scaling, revealing that compute-intensive operators like CRC exhibit super-linear behavior, while most others are sub-linear. We introduce the Operator Performance Quadrant (OPQ) framework to classify operators by base and scaling costs, exposing a cross-architecture Quadrant Shift between Arm and x86. This method provides accurate, architecture-aware bottleneck diagnosis and a realistic basis for performance modeling and optimization. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_09574 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Profiling Multi-Level Operator Costs for Bottleneck Diagnosis in High-Speed Data Planes Ren, Zhiyuan Liu, Yutao Cheng, Wenchi Yang, Kun Signal Processing This paper proposes a saturation throughput delta-based methodology to precisely measure operator costs in high-speed data planes without intrusive instrumentation. The approach captures non-linear scaling, revealing that compute-intensive operators like CRC exhibit super-linear behavior, while most others are sub-linear. We introduce the Operator Performance Quadrant (OPQ) framework to classify operators by base and scaling costs, exposing a cross-architecture Quadrant Shift between Arm and x86. This method provides accurate, architecture-aware bottleneck diagnosis and a realistic basis for performance modeling and optimization. |
| title | Profiling Multi-Level Operator Costs for Bottleneck Diagnosis in High-Speed Data Planes |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2508.09574 |