Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Nebraska football's preseason camp is nearly through the first week, but that has already come with plenty of outside coverage. On Monday, a portion of the practice was open to the local media. On ...

Abstract: As the amount of data and complexity of neural network models continue to grow, distributed training has become increasingly crucial for improving training speed. However, the bottleneck of ...

The researchers stress that this scale of work was made possible by a coordinated ecosystem of computational services: CyVerse for data storage, OSG OS Pool for high-throughput computing, Pegasus for ...

Abstract: Training Graph Neural Networks (GNNs) on large graphs presents unique challenges due to the large memory and computing requirements. Distributed GNN training, where the graph is partitioned ...

Neural Network Training Fingerprint (NNTF) is a visualization approach to analyze the training process of any neural network performing classification.

A new research paper from Canada has proposed a framework that deliberately introduces JPEG compression into the training scheme of a neural network, and manages to obtain better results – and better ...