Figuring out what happens when foreign bodies invade the human body is fairly serious business. Confined mostly to the realm of test tubes, complex reactions like the human immune system responding to a tuberculosis infection have been difficult and time consuming to study – willing volunteers for this kind of study are hard to come by.
Computer modeling has made these trial-and-error type studies easier by being able to replicate a system's response to an introduced external factor -- simply program the behavior of the components of the system and hit the start button.
Agent based modeling may take this kind of systems study to the next level, however, and a team of computer scientists at Michigan Tech University are making it happen without the use of super-powerful, super-expensive supercomputers. Under the direction of Roshan D'Souza, computer science students at MTU have developed agent based modeling software that harnesses the power of modern graphics processing units.
"With a $1,400 desktop, we can beat a computing cluster. We are effectively democratizing supercomputing and putting these powerful tools into the hands of any researcher. Every time I present this research, I make it a point to thank the millions of video gamers who have inadvertently made this possible,” says D'Souza of the project.
Agent based modeling is a very powerful tool in which many different components, factors and behaviors can be programmed and then let loose in a simulated environment. The outcomes of large systems are often unpredictable and surprising.
MTU's software, which was created by computer science student Mikola Lysenko, is not limited to small systems with few factors such as the previous tuberculosis example. Ryan Richards, a fellow computer science student explained, "We can do very complex ecosystems right now. If you're looking at epidemiology, we could easily simulate an epidemic in the US, Canada and Mexico."
It seems the days of supercomputers and complex simulations may be numbered, becoming an endangered species quickly at the hands of the relatively inexpensive gamer's video card. Perhaps the next step in evolution for these modeling software projects could be similar to Stanford's very successful Folding@Home project, using the client's GPU to power its way to understanding new and complex systems.