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Analyzing and Mitigating Data Stalls in DNN Training
of data that can be cached in memory, the number of CPU threads used to fetch and pre-process data, and GPU generation. We then analyze how these factors affect the data pipeline and DNN training. Our analysis shows that data stalls are prominent in popular com-puter vision and audio DNNs, as opposed to text-based NLP models.
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