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Equation 13 · Part 1 · Comparing the Main Approaches to AI Memory Systems and the Bandwidth Wall

Symbol M_kv

Mkv  ≈  2 L H dh b T,M_{\mathrm{kv}} \;\approx\; 2 \, L \, H \, d_h \, b \, T,
MkvM_{\mathrm{kv}}

What this part means

MkM_kv is a part of this expression. Its role is fixed by the surrounding article and by the operations shown in the formula.

Its job in the formula

MkM_kv is a part of this expression. Its role is fixed by the surrounding article and by the operations shown in the formula.

The passage around this formula

None of the four sections above describes a system anyone ships in isolation. A contemporary AI accelerator composes several of these answers on top of each other, for a reason the earlier article in this series already established: capacity and bandwidth are separate constraints with separate symptoms, and a real workload — serving a large language model’s key-value cache is the canonical case — hits both at once. The KV cache for a single sequence grows as Mkv  ≈  2 L H dh b TM_{\mathrm{kv}} \;\approx\; 2 \, L \, H \, d_h \, b \, T. with L layers, H key/value heads, dhd_h head dimension, b bytes per stored element and T tokens of context — a quantity that scales linearly with context length and batch size, and has to be both stored somewhere and…

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