New Computing Cluster Scales Up Infrastructure for Undergrads

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New infrastructure at the University of Maryland is expanding computing access to undergraduate students while allowing machine learning researchers to model more data than ever before.

A computing cluster consisting of 330 Nvidia GPUs—graphical processing units that can perform multiple, simultaneous computations—has nearly doubled the infrastructure’s capacity. These GPUs will be used to solve complex problems in computer vision, cybersecurity and more.

This added computational power has democratized access for undergraduate students, who previously could not use machine learning clusters reserved mainly for graduate students and faculty, says Derek Yarnell, director of computing facilities at the University of Maryland Institute for Advanced Computer Studies (UMIACS).

Yarnell, who led the installation, adds that the new cluster will let machine learning researchers tackle larger data sets with longer and more complicated algorithms.

“This is a significant increase across the board for our entire research community,” he says. “But the cluster’s biggest impact will be in providing new professors and students with access to these powerful tools.”

Mohammad Nayeem Teli, a senior lecturer in the Department of Computer Science, will employ the cluster in his "Introduction to Machine Learning" course this fall. The course requires students to work on multiple machine learning models with large data sets that require faster computational resources as they become more complex. He says that the new cluster will not only enable students to run their models faster, but will enhance their overall performance.

A collaborative effort between the UMIACS and the Department of Computer Science, the $2 million cutting-edge cluster was purchased with remaining computing infrastructure funds from the construction of the Brendan Iribe Center for Computer Science and Engineering.

“We’re excited about expanding our infrastructure to support more of our undergraduate students,” says Mihai Pop, the director UMIACS and a professor of computer science. “This enhancement will not only directly benefit our undergraduates, but advance the level and reputation of machine learning research at the University of Maryland as a whole.”

Story by Maria Herd, UMIACS communications group

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