21 August 2026

PagedAttention brings virtual memory technique to AI model memory

• PagedAttention applies virtual memory concepts, a computer architecture idea, to how AI models store information during processing.
• The KV cache stores key-value pairs that models need to track context, and it consumes substantial GPU memory when processing long texts.
• This technique lets attention kernels (the part computing which words matter most) access memory more efficiently without requiring redesign.

How it was covered

TLDR AITLDR editorial team

The article explains how PagedAttention applies virtual memory concepts to the KV cache, which consumes significant GPU memory at long contexts. The approach allows attention kernels to work with memory efficiently.