PtrainX
PtrainX is a distributed machine learning training framework designed to scale the training of large neural networks across multiple GPUs and compute nodes. It provides a unified programming model that supports data parallelism, pipeline parallelism, and model parallelism, with an emphasis on performance, fault tolerance, and ease of integration with existing workflows.
The framework is designed to interoperate with major deep learning platforms, offering adapters for popular libraries
Key features include automatic mixed precision, gradient accumulation and checkpointing, gradient compression and sparsification, and flexible
History and development notes indicate that PtrainX originated from a collaboration of researchers and practitioners aiming
ptrainx is used in research and industry contexts where scaling deep learning workloads to substantial hardware