SVF scheduling algorithm achieves a competitive ratio of 3 for LLM serving and integrates into vLLM to reduce average and tail latency.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Feather uses reinforcement learning and a Chunked Hash Tree to balance batch size against prefix homogeneity in LLM inference, delivering 2-10x higher throughput than existing schedulers.
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Geometry-Aware Online Scheduling for LLM Serving: From Theoretical Bound to System Practice
SVF scheduling algorithm achieves a competitive ratio of 3 for LLM serving and integrates into vLLM to reduce average and tail latency.
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Requests of a Feather Must Flock Together: Batch Size vs. Prefix Homogeneity in LLM Inference
Feather uses reinforcement learning and a Chunked Hash Tree to balance batch size against prefix homogeneity in LLM inference, delivering 2-10x higher throughput than existing schedulers.