Distributed Data Parallelism (Distributed Parallel Training, often abbreviated as DDp) represents a significant technique for scaling machine learning model training across multiple devices, like GPUs or machines. https://ddp823702.veronicablog.com/61909439/parallelism-explanation-to-parallel-processing