Expanding Deep Learning

Powerful new GPU cluster advances regional deep learning research

Deep-learning research uses neural network algorithms to analyze large data sets. With a new cluster of 400 specialized graphics processing units (GPUs), our campus has a powerful new tool for big data analysis and is poised to attract the nation’s next crop of top PhD students and researchers in deep-learning fields. Housed at the Massachusetts Green High Performance Computing Center in Holyoke, Massachusetts, the cluster is the result of a five-year, $5 million capital grant to the campus from the Baker administration and the Massachusetts Technology Collaborative. The grant leverages a $15 million gift supporting data science and cybersecurity research from the MassMutual Foundation of Springfield.

Unusually large for an academic cluster, the GPUs are critical for modern computer science research because of their enormous computational power. According to computer scientist and project lead Erik Learned-Miller (above), they can address extreme computational needs, solving problems 10 times faster than conventional processors.

“Deep learning is a revolutionary approach to some of the hardest problems in machine reasoning and is the ‘magic under the hood’ of many commercial products and services,” says Learned-Miller. “Google Translate, for example, produced more accurate and natural translations thanks to a novel deep-learning approach.”

The campus currently has research projects that apply deep learning techniques to computational ecology, face recognition, graphics, natural language processing, and many other areas.

Learned-Miller says he and colleagues are now in the first year of the grant, during which about $2 million has been spent on two clusters: the GPU cluster, dubbed “Gypsum,” and a smaller cluster of traditional CPU machines dubbed “Swarm II.” Gypsum consists of 400 GPUs installed on 100 computer nodes, along with a storage system and a backup system. It is configured with a leading software package for deploying, monitoring and managing such clusters.

Not only do the researchers hope the GPUs will accelerate deep learning research and train a new generation of experts at the campus's College of Information and Computer Sciences, but an important overall goal is to foster collaborations between the campus and industry. Connect with our Center for Data Science.