Yuchen Fama

Learn how to optimize deployment of vLLM for various traffic shapes, including high-concurrency chat, long-context RAG, high-throughput batch, and distributed AI-grid.

Learn about the three optimization levers for distributed AI inference: prefill/decode disaggregation, KV cache strategy, and speculative decoding.

Learn about the five-dimensional design space in modern LLM serving, including tensor, pipeline, expert, data, and context parallelism.

Learn how to run OpenAI's Whisper model through vLLM on Apple Silicon, giving you an OpenAI-compatible endpoint on localhost. Then, discover how to take this architecture into production using Red Hat AI Inference Server.