A manufacturer has deployed an array of 50000 sensors throughout its plant to predict failures in components. Data Scientists have built a long short-term memory (LSTM) model in Gluon and are training

A manufacturer has deployed an array of 50000 sensors throughout its plant to predict failures in components. Data Scientists have built a long short-term memory (LSTM) model in Gluon and are training it using the Amazon SageMaker API. The Data Scientists are training the model using a time series with 10 million examples. Training is currently taking 100 hours and Data Scientists are attempting to speed it up by using multiple GPUs. However, when they modified the code to use 8 GPUs, it is running slightly slower than on 1 GPU. The current hyperparameter settings are:

Hyperparameter Value Batch size 128 Clip gradient 10 Autoregressive window 160 Learning rate 0.01 Epochs 80 Which of the following changes together are recommended to speed up training on 8 GPUs while maintaining test accuracy? (Select TWO)