Calibrated Router Boosts LLM Serving Efficiency
A study examines a new approach to routing requests in disaggregated Large Language Model (LLM) serving systems. The researchers developed a router that uses various metrics like prompt length and predicted output length to estimate the additional completion time on each instance. They validated this policy using an event simulator with NVIDIA A40 GPUs, which handle different workloads at full…
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Key points
- Calibrated router achieves highest mean goodput at 0.864
- Outperforms traditional methods like round robin and length heuristic
- Hardware calibration is crucial for optimal performance
Read the original at arXiv cs.AI · by Srikanta Datta Tumkur, Jay Iyer, Mehar Simhadri, Sai Pavan Kumar, Sai Kapil Kumar, Ramesh Nampelly primary source Open source ↗
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