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The rate at which data can be read and re-read from storage can limit training performance. The key to performance is the ability to read data multiple times, ideally from local storage. The closer the data is cached to the GPU, the faster it can be read. Storage must be designed considering the hierarchy of different storage technologies, either persistent or nonpersistent, to balance the needs of performance, capacity, and cost.