vLLM: Anatomy of a High-Throughput LLM Inference System
From paged attention, continuous batching, prefix caching, specdec, etc. to multi-GPU, multi-node dynamic serving at scale.
Summary
The article details the technical components of a high-throughput inference system for large language models, including advanced techniques like paged attention and prefix caching. It also covers the challenges and solutions for scaling across multiple GPUs and nodes.
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