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PEEK maintains an incremental radix tree over the pending queue, exposing\n  prefix-sharing clusters no existing engine surfaces. A low-overhead dual-walk matches the tree against the engine's prefix cache to yield longest-prefix-match for every waiting request; PEEK then admits cluster pioneers first so siblings\n  inherit the freshly cached prefix, a co-designed eviction hook protects blocks ancestral to queued demand, and a multi-lane stride scheduler bounds starvation. On SGLang and vLLM across five workloads up to 4$\\times$H100 (DP=2 over TP=2),\n  PEEK delivers up to 3.0$\\times$/2.6$\\times$ cache hit, 7.9$\\times$/7.1$\\times$ TTFT, 6.7$\\times$/5.5$\\times$ E2E, and 3.6$\\times$/4.5$\\times$ throughput gains over each engine's strongest stock baseline (SGLang/vLLM), while m","title":"PEEK: Predictive Queue-Informed KV Cache Management for LLM Serving","url":"https://arxiv.org/abs/2607.02525","vendor":"arxiv_cs_ai"},"summary":"arXiv:2607.02525v1 Announce Type: cross \nAbstract: We present PEEK, a lightweight scheduling and eviction framework for both online (streaming) and offline (batch) LLM serving; this paper focuses on the online regime. PEEK maintains an incremental radix tree over the pending queue, exposing\n  prefix-sharing clusters no existing engine surfaces. A low-overhead dual-walk matches the tree against the engine's prefix cache to yield longest-prefix-match for every waiting request; PEEK then admits cluster pioneers first so siblings\n  inherit the freshly cached prefix, a co-designed eviction hook protects blocks ancestral to queued demand, and a multi-lane stride scheduler bounds starvation. 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