This node focuses on the use of modern machine learning and deep learning frameworks in HPC contexts. It includes practical usage of PyTorch and TensorFlow, as well as strategies for scaling training across distributed systems.

• Use leading ML/DL frameworks to define, train, and evaluate models.
• Apply distributed training strategies using framework-native tools for scalability and performance.

• BDA5.3.1 Pytorch
• BDA5.3.2 Tensorflow
• BDA5.3.3 Distributed Training

Caution: All text is AI generated