What does this equation mean?

The key-value cache is the part of a serving system’s memory footprint that a purchasing decision cannot fix, because it does not exist until a request is running. It grows with every generated token, in proportion to context length, batch size, layer count and head dimension, and its lifetime is exactly the lifetime of the request that owns it — arriving and departing unpredictably, at whatever size that request’s conversation happens to reach. A capacity plan sized for the average context length will be wrong for the tail, and a naive contiguous allocator sized for the tail will waste most of its memory on requests that never reach it. with L transformer layers, H key-value heads, $d_h$ head dimension, b batch size, s sequence length and p bytes per stored element, the factor of two counting keys and values separately. Every strategy below is, mechanically, an attempt to shrink one term of this product without shrinking the model’s effective context.