UAB IT’s Research Computing team works to help researchers across the university grow in their areas of investigation by facilitating technology tools individualized to the researchers’ needs.
“There’s no charge for our investigators to use these resources,” said Ralph Zottola, Ph.D., assistant vice president for research computing. “That is not to say that it is free—it’s ‘pre-paid’. We are fortunate to be at a place like UAB that supports research computing services for all faculty and students. Our group strives to achieve the best outcomes for the research community.”
Ari Ginsparg, a Ph.D. student working with neurobiology professor Summer Thyme, Ph.D., began his thesis at UAB focusing on computational drug discovery, which consisted of algorithm and pipeline development. While at UAB, Ginsparg collaborated with Research Computing and began using the tools curated by the team to help bring his investigation to a larger scale. The team also helped make sure it would be able to move to a new lab when the time came.
“I learned about the Research Computing team during my second lab rotation; it was very computational and used Cheaha frequently,” Ginsparg said. “So, when I began to scale up the size of my pipeline in early 2021, I realized I could benefit from using it myself.”
The algorithm Ginsparg created while at the university is used to identify ligands, which are molecules that bind to a receptor that has an agonistic effect on Hypocretin Receptor 2 (HCRTR2). The hope of this research is to remedy narcolepsy and confirm if the actions do occur during this protein exchange.
While conducting research, Ginsparg knew he needed to store large amounts of data — using more than 75TB. Research computing created a “long-term storage” (LTS) service that allows investigators to store and access massive amounts of data. Ginsparg collaborated with the Research Computing team to leverage that service.
When it came time to scale the research up, Prema Soundararajan, a scientist within Research Computing, and her team helped Ginsparg leverage the Open Science Grid, or OSG.
“The Open Science Grid functions on a much larger scale than Cheaha due to being composed of sections from multiple supercomputers to efficiently tackle many smaller tasks, approximately 10,000 jobs, simultaneously. It requires fewer computing resources per job, making it well-suited for high-throughput applications,” said Soundararajan. "Cheaha effectively solves large and complex problems that need a lot of computing resources. Despite its capabilities, it maintains a user limit of 250 parallel jobs to fairly serve the diverse needs of all UAB users. This makes Cheaha especially suitable for high-performance applications."
The Open Science Grid started in 2005 and is used by scientists and researchers around the world for data analysis tasks which are too large for a single data center or supercomputer. Ginsparg said OSG is like having “multiple Cheahas put together,” meaning that it can perform computational operations at a larger scale than the one single supercomputer.
“We have designed our infrastructure to tie into our national computing resources, which allows our investigators to scale their work up when they need a lot more computing,” Zottola said. “We’re lucky to be able to support our researchers in this way, with these pre-paid resources. This will help them when it comes time to deploy their work to a national level, as well as extend the university’s investments in Research Computing.”
In late 2023, Ginsparg moved to the University of Massachusetts to continue his research. Because of his early exposure with OSG with help from Research Computing, he now serves in an advisory group aimed to help guide the future of the grid.
To learn more about using Cheaha and other Research Computing resources, visit our website.