Training at Scale

Back: Deep Learning

Techniques and infrastructure for training large models across multiple GPUs and machines. Essential for modern foundation models that require enormous compute.

Concepts

• Data Parallelism
• Model Parallelism
• Mixed Precision Training
• Gradient Accumulation
• Distributed Training Frameworks
• Deep Learning Frameworks

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deep-learning distributed-training scale