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minibatch-persistency

topic1 events
papersTODAY 04:00 UTC

Minibatch persistency revisited: trade-offs in steps, energy and data use

A new arXiv paper re-examines minibatch persistency, a technique where the same batch is reused for K consecutive optimizer steps rather than sampling fresh data each time. The authors quantify what batch reuse costs in terms of optimization steps and energy consumption, and what it saves in data throughput. The work revisits a long-standing objection to the method, which was folded into data echoing in 2019.

training/efficiency/batch-reuse/arxiv