vLLM Speeds Up LLM Inference with Push-Based KV Transfer
vLLM's prefill-decode disaggregation now handles KV cache transfers more efficiently using a push-based NIXL connector that removes bottlenecks from the critical path. On AWS EC2 P5en instances with EFA, this approach delivers up to 3x faster time-to-first-token (TTFT) and 30% better throughput per output token (TPOT).
source: [aws/machine-learning-blog]