"Basically, Big-STEM means we can solve problems that pretty much no one else is working on", stated computer science professor Jim Alves-Foss, who manages the Big-STEM project for the group of research faculty who will tap into its power to more quickly churn through data sets so complex they would fry lesser systems.
Big-STEM's power lies in its incredible amount of memory. When it's complete, Big-STEM will have 8 terabytes of memory - 4,000 times the memory of the average home computer.
A grant from the National Science Foundation funded an initial 4-terabyte phase that enabled University of Idaho professors last fall to begin testing its potential. University of Idaho received additional funding this month from the Murdock Charitable Trust to add a second 4-terabyte phase.
While other types of supercomputers can handle huge amounts of data, Big-STEM's big memory allows it to address problems that involve massive interactions among data, such as detailed simulations and models of complicated systems.
"There's a whole range of complex problems that people haven't been able to find solutions to because the computing power wasn't there", Jim Alves-Foss stated. "Some of our faculty members are working on these problems. They're on the cutting edge of research."
"This machine gives us the capacity to work on problems that are important to industry, too, supporting Idaho Global Entrepreneurial Mission (IGEM) initiatives sponsored by the Idaho Legislature", he added.
Several faculty members are already putting Big-STEM to work, including researchers designing thermo-electric devices to improve vehicles' fuel economy, creating advanced river-flow models and studying large particle systems.
Marty Ytreberg, University of Idaho associate professor of physics, studies proteins found in the human body that rapidly change shape. Many of these types of proteins are implicated in human disease, and understanding them could help researchers design specially targeted drugs.
However, one single protein can have as many as 100,000 different shapes. If Marty Ytreberg tried to give even a very powerful common computer the task of finding similarities within the protein structures, it would run out of memory and crash. But Big-STEM is up to the task.
"I can do analysis on Big-STEM that I can't do on any other computer", he stated.
Projects like Marty Ytreberg's are only the beginning. Jim Alves-Foss said Big-STEM's abilities put it on par with some of the nation's highest-performing computing clusters - such as the 8-terabyte Mason system at Indiana University - meaning it offers rare opportunities for research.
It is amazing what we can do with modern computing", Jim Alves-Foss stated. "So often I am reminded that we have brilliance and tremendous capability all across our country, and not just in the Ivy-League schools. I am proud to be part of this group and to help our talented young faculty realize the full potential of their research."