Introduction to distributed inference with llm-d

This blog post provides an in-depth introduction to distributed inference with the open-source project llm-d, which aims to improve the deployment of large language models (LLMs) through more efficient resource distribution and scheduling. It discusses the evolution of distributed computing, particularly through Kubernetes and OpenShift, and introduces llm-d's innovative approaches like disaggregated inference and intelligent routing. By optimizing performance across a hybrid cloud platform, llm-d enables organizations to scale their AI applications more effectively.