vLLM V1: Serving LLMs Efficiently at Scale

Ubicloud's open-source cloud service leverages vLLM V1 to serve large language models efficiently. This article delves into the vLLM V1 architecture, detailing the journey of an inference request from reception, scheduling, and model execution to output processing. Key technologies like asynchronous IPC, continuous batching, and KV cache management are explained. vLLM V1 maximizes GPU utilization through asynchronous processing, a continuous batching algorithm, and parallel GPU computation, enabling high-throughput text generation at scale. This provides valuable insights for AI engineers deploying LLMs and those interested in understanding how large language models are served efficiently.
Read more