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Equation 1 · Part 4 · How AI Memory Systems and the Bandwidth Wall Actually Work

Symbol B

I=FLOPs performedbytes moved,Pachievable=min⁡(Ppeak compute,  I×BWpeak memory)I = \frac{\text{FLOPs performed}}{\text{bytes moved}}, \qquad P_{\text{achievable}} = \min\left(P_{\text{peak compute}},\; I \times BW_{\text{peak memory}}\right)
BB

What this part means

B appears in the objective or constraint used by the optimization on the right.

Its job in the formula

B appears in the objective or constraint used by the optimization on the right.

The passage around this formula

The roofline model, introduced by Williams, Waterman, and Patterson in 2009, gives the concept its formal shape. It plots two independent ceilings on the same chart: the chip’s peak arithmetic throughput (operations per second) on one axis, and its peak memory bandwidth (bytes per second) combined with a workload-specific ratio on the other. That ratio — arithmetic intensity — is defined as the number of floating-point operations performed per byte of data moved between memory and the arithmetic units [ 4 ] . A workload’s achievable throughput is bounded by whichever ceiling it hits first: I=FLOPs performedbytes moved,Pachievable=min⁡(Ppeak compute,  I×BWpeak memory)I = \frac{\text{FLOPs performed}}{\text{bytes moved}}, \qquad P_{\text{achievable}} = \min\left(P_{\text{peak compute}},\; I \times BW_{\text{peak memory}}\right). When a workload’s intensity I is high enough that I ×\times BWpeak memoryW_{\text{peak memory}}…

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Sources cited in the surrounding passage

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