Push-based KV transfer to improve TTFT and TPOT for disaggregated inference in vLLM

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vLLM is an open-source inference and serving engine for large language models (LLMs). LLM inference has two distinct phases: prefill, which processes the input prompt and builds the key-value (KV) cache, and decode, which uses that cache to generate output one token at a time. These phases have different compute, memory, and scaling characteristics. Prefill-decode (P-D) disaggregation runs them on separate engine instances, allowing each phase to scale and be optimized independently. This can…