AI Research
Decode-Latency Feedback Prefill: A Model-Free Controller and Its Generalization Limits
Optimizing LLM serving throughput by balancing prompt prefill interference and active decoding latency.
Concurrent autoregressive inference creates a fundamental interference problem: prefilling a newly arrived long prompt can delay tokens for requests that are already decoding. Fixed prefill chunks reduce this interference, but the best chunk size depends on the model, hardware, l...
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ArXiv CS.AI
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ArXiv CS.AI
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This research addresses the critical bottleneck of resource contention in LLM serving, where new prompts interrupt active token generation. By introducing a model-free controller, it paves the way for more predictable, low-latency inference in multi-tenant AI deployments.
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