How can KV-store optimizations speed up long-context LLMs

Question

Can i know How can KV-store optimizations speed up long-context LLMs?

Answer 1

You can speed up long-context LLMs by caching and reusing key-value (KV) pairs in attention layers to avoid redundant computation over previous tokens.

Here is the code snippet below:

In the above code, we are using the following key points:

• kv_cache stores past key and value tensors to reduce recomputation.

• Attention computation is optimized by concatenating cached and new KV pairs.

• Cache updating uses detach() to avoid backward path through cache.

Hence, KV-store optimizations enhance efficiency in long-context LLMs by eliminating repeated attention over prior tokens during inference.