How vLLM Works + Journey of Prompts to vLLM + Paged Attention

Описание: In this video, I break down one of the most important concepts behind vLLM’s high-throughput inference: Paged Attention — but instead of explaining it with dry theory, we follow the story of three prompts traveling through the vLLM engine.

You’ll see how:

Each prompt gets its KV cache blocks allocated

How slot mapping connects logical token positions to physical locations in GPU memory

Why block reuse and block management make vLLM extremely fast

How decoding and prefilling can happen in the same step thanks to vLLM’s architecture

And how everything fits together to maximize efficiency

Whether you're building LLM apps, optimizing inference, or just curious about how modern LLM engines work behind the scenes, this visual journey will make Paged Attention finally click.


#vLLM #PagedAttention #LLMInference #AIEngineering #MachineLearning #DeepLearning #AIModels #LLMOptimization #AIInfrastructure
#ArtificialIntelligence #NeuralNetworks #TechExplained #AIVideo #MLTutorial #AIVisualization #ComputerScience #GPUComputing #PythonAI