SemiAnalysis 发文指出,稀疏注意力(sparse attention)主要帮助解决内存带宽问题,并不能缓解内存容量瓶颈。其引述的观点解释称,HiCache 的思路是把 KV cache 从 HBM 卸载到容量更大但带宽更低的存储层级,计算时只加载最相关的 token;由于稀疏注意力计算中仍需选择 token,所有 token 都不能丢弃,最终仍要加载进 HBM。
AI 生成摘要 · 以原文为准
Sparse attention fixes memory bandwidth, not memory capacity.
“The whole idea of HiCache is trying to offload KV cache from the HBM to a lower tier, higher capacity but lower bandwidth memory, and only load the most relevant set of tokens during computation.”
“Sparse attention doesn’t mitigate the memory capacity bottleneck. It’s a technique that helps a lot with memory bandwidth.”
“During the sparse attention computation, you still need to select the tokens. So you still have to keep all the tokens in context, and you cannot discard them. At some point, it still has to be loaded into HBM.”
“That’s where HiSparse becomes useful, because it can apply the typical caching rules so that you could load the most relevant parts into HBM.”
来源:SemiAnalysis · x.com