Senthilkumar Gopal

This post explains how Paged Attention and Chunked Prefill optimize memory and computation in vLLM by organizing key-value caches into dynamic blocks and processing input sequences in manageable chunks. It includes a simple walkthrough with tensor shapes and code to showcase their integration for LLM inference.

A quick clarification between the terms - Triton, TensorRT, and TensorRT-LLM