Thursday, September 12, 2013 - 10:21am

Building on the success of its first high-performance computing (HPC) cluster, the University of Iowa is now building a second “supercomputer” that will be available to researchers early next year.

The UI’s first HPC cluster, Helium, came online in 2011, and with rapid increase in usage by UI researchers is now operating near capacity, at more than 90 percent utilization. The state Board of Regents on Wednesday approved the purchase of the new system, Neon. The addition of Neon will significantly boost the university’s HPC capacity from 3,700 to 6,132 processor cores.

HPC supports research that would not otherwise be possible at the UI, in some cases condensing the time required to run simulations from years to days by using multiple processors that work on single or multiple computational tasks at the same time. UI investigators use Helium for a wide variety of projects, like modeling flood scenarios to help Iowa communities make decisions about mitigation, understanding how uterine cancer develops, and modeling climate change and airflow in the lungs.

Twenty-five research groups from seven UI colleges have already invested $700,000 in the new system. The university centrally funded the remaining $500,000 of Neon’s total $1.2 million cost. The system will have a safe, secure home at the UI’s new Information Technology facility, and will be administered and maintained by the Information Technology Services (ITS) Research Services team.

"The decision to invest in Neon is based on the tremendous success we've experienced with Helium," says P. Barry Butler, executive vice president and provost. "By matching central resources with faculty-generated grants we've been able to build a shared, high-performance computing environment that's available to all faculty, whether they have grant funding or not. The efficiency of this approach to shared investment is something I think the university should be very proud of."

History and rapid growth of HPC at the UI

HPC got its start at the UI two years ago, when the Institute for Clinical and Translational Science, IIHR-Hydroscience and Engineering, and ITS-Research Services teamed up to launch Helium.

The initial investment that made Helium possible came from a faculty member in the College of Engineering, and investments from a dozen other researchers followed, providing the startup funds. A centrally funded expansion of the system in fall 2011 opened it up to users across the institution.

Use of Helium increased dramatically in its first year. By the end of 2012, the system had provided 2,200 compute years of service, up from just 250 its first year. The number of users soared from about 50 in 2011 to 250 in 2012, and the user base now represents 52 units from all across campus.

Today Helium consists of 3,700 processor cores and over 500 terabytes of data storage. It provides over 2 million compute hours per month to UI researchers. At current market rates, utilizing external HPC resources such as Amazon’s compute service would cost the UI over $300,000 per month.

The installation of Neon, built using the latest generation of compute, storage, and network hardware, will help meet the increased demand for HPC capabilities on campus by providing an additional 2,432 processor cores, 1,440 co-processor cores, 7,488 Graphics Processing Unit (GPU) cores, access to large amounts of memory, and 216 terabytes of storage capacity.

HPC success stories

One example of HPC usage on campus is to study changes in the brains of Huntington disease (HD) patients before they begin to experience symptoms. The research could lead to earlier interventions for people diagnosed with the hereditary disorder, which causes widespread brain tissue atrophy, interfering with mobility, memory, speech, and mood.

The PREDICT-HD study involves 1,500 research subjects worldwide. Researchers analyze brain scans from the patients over a 10-year period and apply algorithms to extract measurements that quantify the progression of the disease. Measurements include changes in brain volume, tissue composition, structural size, anatomical regions, and cortical depth. Researchers then look at how changes in different regions of the brain correlate with psychiatric, behavioral, and cognitive measures.

Testing each algorithm’s effectiveness takes more than 42 hours of computation per imaging scan session. There are 4,400 data sets to test with each method, and many parameters to modify.

“Testing the algorithms on a single computer would take two or three years of data processing,” says Hans Johnson, Ph.D., an assistant professor of psychiatry. “HPC allows us to do that in one day.”

For more stories on HPC research and details about UI HPC resources, visit