Data Movement Is All You Need: A Case Study on Optimizing Transformers

30 Jun 2020Andrei IvanovNikoli DrydenTal Ben-NunShigang LiTorsten Hoefler

Transformers have become widely used for language modeling and sequence learning tasks, and are one of the most important machine learning workloads today. Training one is a very compute-intensive task, often taking days or weeks, and significant attention has been given to optimizing transformers... (read more)

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