Abstract: The importance of Model Parallelism in Distributed Deep Learning continues to grow due to the increase in the Deep Neural Network (DNN) scale and the demand for higher training speed.
Abstract: The ever-increasing computational complexity and energy consumption of today’s applications, such as machine learning (ML) algorithms, not only strain the capabilities of the underlying ...
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