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with the per-step latency and the per-link bandwidth. The bandwidth term approaches 2N/ and stops growing with p ; the latency term grows linearly in p . Small, frequent collectives are therefore latency bound and scale badly, while large ones are bandwidth bound and scale well — which is precisely why gradient bucketing and overlapping communication with backward computation are standard practice rather than optimisations.
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Equation 33 · AI Hardware & Semiconductors
What an AI Accelerator Actually Is: Silicon, Packaging, and the Memory It Can Reach
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with the per-step latency and the per-link bandwidth. The bandwidth term approaches 2N/ and stops growing with p ; the latency term grows linearly in p . Small, frequent collectives are therefore latency bound and scale badly, while large ones are bandwidth bound and scale well — which is precisely why gradient bucketing and overlapping communication with backward computation are standard practice rather than optimisations.