How Hyperparameter Optimization Improves Machine Learning Accuracy

In January, a team of Cray developers and researchers published a paper, “Recombination of Artificial Neural Networks,” on, highlighting the hyperparameter optimization (HPO) capability Cray announced in November. We cover their findings in this blog post. Using a variety of high-performance computing systems and neural network models, the Cray team demonstrated that the hyperparameter optimization capabilities introduced in the Cray® Urika®-CS and Urika®-XC AI and analytics software suites improve the time-to-accuracy as well as final accuracy of machine learning models trained on Cray systems. The table below, excerpted from the paper, highlights the improvements achieved using Cray’s HPO capability across a range of ... [ Read More ]

Deep Learning at Scale Using Cray Distributed Training

This article was written by the following Cray and NERSC contributors: Steve Farrell, Machine Learning Engineer; Thorsten Kurth, Application Performance Specialist; Jacob Balma, Performance Engineer; Peter Mendygral, Performance and Software Engineer; Nick Hill, Software Engineer. Deep neural networks (DNN) are revolutionizing science across many domains including high energy physics, cosmology, biology, and climate. As the field of deep learning advances, DNN architectures grow more sophisticated and capable of solving complex tasks in scientific problems such as classification, regression, and simulation. Training and evaluating such models requires increasingly large datasets and computing resources. Through the NERSC Big Data ... [ Read More ]

What We Want to Learn at the Biggest AI Summit of the Year

What’s top of mind for AI-focused data scientists and experts right now? NeurIPS – the biggest artificial intelligence summit of the year. The 32nd annual Conference on Neural Information Processing Systems gets underway Dec. 2 in Montréal. Like most organizations involved with artificial intelligence, we have a team here at Cray gearing up for the event. With that in mind I thought it would be interesting to get their before and after perspective. I asked four members of our NeurIPS-bound team a simple question: what are you looking forward to learning at the event? Here’s what they said: Per Nyberg, Vice President Market Development, Artificial Intelligence and Cloud I’m most interested in learning about progress and new ... [ Read More ]

When It Comes to AI, Automation Is Better, Choice Is Good, and Simplicity Is King

This week at the SC18 supercomputing event, one of the exciting areas we’re highlighting is how Cray continues to expand its artificial intelligence portfolio to support researchers, data scientists and IT teams as machine and deep learning become core to their everyday missions. As we’ve spoken to organizations starting out with AI, developing models, doing real research, or implementing production systems, we’ve noticed a few themes: • Machine learning is as much an art as it is a science, and a time-consuming endeavor at that. Automation tools that help the data scientist get to the optimal solution faster are much appreciated. • No single “right” tool set exists. Some teams prefer TensorFlow, some PyTorch, some Apache Spark™ ... [ Read More ]

Learning About Learning: Artificial Intelligence, Machine Learning & Deep Learning

Artificial intelligence (AI), machine learning (ML) and deep learning (DL): these terms crop up often online and in the popular and technical media. They either represent a tidal wave that’s going to overwhelm every industry and company that doesn’t rapidly adapt or they’re a more incremental innovation in IT. They may usher in new capabilities like speech recognition or image analysis, but at the same time they may also be a little overhyped today. Which of these scenarios is closer to reality? And while we’re at it, what — if anything — are the differences between AI and machine learning and deep learning? Also, why does any of this matter to someone who’s otherwise interested in high-performance computing and IT at the cutting edge? ... [ Read More ]