KV cache management is arguably one of the hardest problems in LLM inference, and advancing it requires the community to learn from and build on one another’s work. Great to see that happening. Amazing work from
@lightseekorg on adopting and evolving vLLM's hybrid memory allocator!
The Jenga paper from
@ChenZha62999224 is especially relevant today as attention architectures become increasingly complex.