PyTorch Distributed
PyTorch Distributed is a PyTorch module that provides distributed training capabilities for deep learning models across multiple GPUs, nodes, or clusters. It enables parallel processing to accelerate training, handle large datasets, and scale models beyond single-machine limits. The framework includes communication primitives, data parallelism strategies, and tools for managing distributed environments.
Developers should learn PyTorch Distributed when training large-scale deep learning models that require significant computational resources or memory, such as in natural language processing (e.g., GPT models) or computer vision (e.g., high-resolution image models). It is essential for reducing training time through parallelism, enabling experiments with massive datasets, and deploying models in production environments that demand scalability across multiple machines.