Researchers at the University of Texas at San Antonio (UTSA) are using high-performance computing to reverse-engineer brain neurons, in a quest to build better computers.
A team within UTSA's biology department is taking advantage of powerful parallel computers to run realistic simulations of molecular diffusion in neurons. By understanding how neurons process chemical signals when a person learns and remembers information, researchers believe they can create more reliable computers that employ statistical methods, called Monte Carlo simulations, to solve problems.
However, the brain contains trillions of different neurons that branch off and connect to each other, so running these simulations for each neuron required enormous processing power and memory resources. To solve this, the group used the Star-P software from Interactive Supercomputing to link their desktop computers to an eight-processor parallel computing cluster.
The software allows the team to run Matlab applications on the parallel cluster, with little modification to the original code. So far, the team has doubled its productivity in some areas. The results have been so successful that the team is now going to upgrade its cluster to include 120 processors.
UTSA's work could also lead to other neurobiological research breakthroughs, particularly in realms of sensory acquisition, motor learning, disease, and higher cognitive functions.
