As ML on structured data becomes prevalent across enterprises, improving resource efficiency is crucial to lower costs and energy consumption. Designing systems for learning on structured data is challenging because of the large number of models. Parameters and data access patterns. We identify that current systems are bottlenecked by data movement which results in poor resource utilization and inefficient training.
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