Unlock 90% KV Cache Hit Rates with llm-d Intelligent Routing скачать в хорошем качестве

Unlock 90% KV Cache Hit Rates with llm-d Intelligent Routing

Maximize your LLM performance with intelligent context routing! 🚀 In this video, Phillip Hayes (Red Hat) demonstrates how llm-d transforms the efficiency of multi-turn conversations and large-document processing. While standard vLLM deployments often rely on naive load balancing that can lead to redundant computations, llm-d introduces a smarter way to manage your replicas. ⚫️ The Context Challenge: See what happens during multi-turn chats when prompts containing large code snippets or Markdown files are sent to replicas that haven't seen that data before. ⚫️ Intelligent Routing in Action: Watch llm-d automatically direct prompts to the specific replica where the context is already cached. ⚫️ Performance Breakthroughs: We track the real-time data from initial turns to completion, showcasing how llm-d achieves a near 90% KV cache hit rate. ⚫️ User Experience Wins: Compare the graphs to see how we slashed P95 tail latency by 500 milliseconds, resulting in a smoother, faster "Time to First Token" for users. Context reuse jumped from roughly 50-60% to nearly 90%. Transitioned from erratic, "spiky" response times to a smooth, predictable performance curve. Significant drops in both P50 and P95 metrics, removing the "laggy" feel from long-form chat. LLM-D ensures that your compute power is used for generating new ideas, not re-processing old ones. If you found this walkthrough helpful, don't forget to Like, Subscribe, and join our community to stay updated on the latest llm-d features! Join the llm-d community: 🌎 https://llm-d.ai 💬 https://inviter.co/llm-d-slack 💻 https://github.com/llm-d