What is PagedAttention, and why did it transform LLM serving throughput?
In naive LLM serving most GPU memory bleeds away to KV-cache fragmentation. PagedAttention adapts virtual memory paging to win it back. What matters is explaining the fragmentation problem and how blocks resolve it.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
In naive LLM serving most GPU memory bleeds away to KV-cache fragmentation. PagedAttention adapts virtual memory paging to win it back. What matters is explaining the fragmentation problem and how blocks resolve it.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
