GPU Training

GPU training focuses on accelerating the computationally intensive process of deep learning model development by leveraging the parallel processing power of graphics processing units. Current research emphasizes optimizing training for various architectures, including transformers (especially large language models), graph neural networks (GNNs), and recommendation models, addressing bottlenecks like communication overhead and memory limitations through algorithmic and system-level innovations such as compressed communication and efficient data management strategies. These advancements significantly impact the feasibility and speed of training large-scale models, enabling faster research cycles and deployment of powerful AI applications across diverse fields.