As many as 5.2-million Americans live with Alzheimer’s disease, according to a 2008 report by the Alzheimer’s Association. Worldwide it is the sixth leading cause of death. Commonly described as “going dark,” Alzheimer’s can make it difficult or impossible to live a fully independent life.
Using technology made available on the TeraGrid, Mu-Hyun Baik, associate professor of chemistry and informatics at Indiana University (IU), is working on the front lines of Alzheimer’s research, helping to bring light to Alzheimer’s patients and their loved ones.
Currently, nobody knows with certainty what microscopic events lead to brain damage. With support from the Research Corporation and Alfred E. Sloan Foundation, however, Baik’s work has simulated the structure of the amyloid-ß protein, widely believed to be the cause of Alzheimer’s disease.
“At the moment, scientists are fishing in the dark,” says Baik. “We don’t even know what the amyloid-ß deposits in the brain look like. Rationally thinking about a treatment or even a cure is impossible. The only hope in this situation is that we find a treatment by accident, which is a very shaky proposition. We need to better understand how amyloid-ß behaves chemically in the brain in order to find a systematic path to treatment and cure.”
This type of fundamental research requires enormous computational infrastructure. “The combination of the advanced computing capability of the TeraGrid,” says Baik, “and the high performance data-storage solution provided by the Data Capacitor was critical. Without it, I would have never dared to begin this project.”
Working with TeraGrid staff, Baik’s amyloid-ß protein analysis was achieved with a workflow that involved using the Data Capacitor, a TeraGrid resource developed at IU, along with IU’s Big Red supercomputer. The massive volumes of data produced by Baik’s computational experiments were managed using a Lustre wide-area file system—an approach that was largely untested at the time.
The payoff for this experimental approach was huge, as Baik demonstrated along with a team from IU, PSC, and ORNL at the Bandwidth Challenge competition held at the 2007 Supercomputing conference in Reno, Nevada. Running data from Baik’s simulations along with a variety of other workflows, the Data Capacitor achieved a staggering bi-directional data transfer rate of 18.2 gigabits per second out of a possible 20. The team clinched the competition using this new model for gathering data from remote resources, and demonstrated the potential of TeraGrid resources for supporting this type of data intensive research.
“The ability to move so much data quickly and easily has already been a tremendous benefit to our research,” says Baik. “We have recently completed the first phase of our work and proposed for the very first time a high-resolution structure of the amyloid-ß deposit. This work is currently being reviewed for publication and our initial conclusions are quite unexpected. We’re on a path toward making some very important discoveries that could change the lives of those suffering from Alzheimer’s disease. This was a new direction in my research that was only possible because I have access to TeraGrid resources.”
Mu-Hyun Baik - http://info.chem.indiana.edu/sb/page/normal/757.html
NSF GSS Codes:
Primary Field: Clinical Medicine (717) - Neurology
Secondary Field: Computer Science (401) - Data Modeling