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YORKTOWN HEIGHTS, N.Y.—Just five years after it began a project to develop the next generation of supercomputers, IBM announced in early June a joint research effort with Switzerland's The Ecole Polytechnique Fédérale de Lausanne (EPFL), to begin building a detailed model of the largest and most complex part of the human brain, the neocortex. The project, dubbed "Blue Brain", will employ the staggering computing capacity of IBM's eServer Blue Gene supercomputer. The system deployed at EFPL occupies a space about the size of four refrigerators and, according to IBM, has a peak processing speed of 22.8 teraflops, or 22.8 trillion floating point operations per second.
 
Renowned neuroscience researcher Henry Markram, professor at EPFL and co-director of the Brain Mind Institute, will lead the research project. "Henry is the person at the forefront of research and has developed a comprehensive set of empirical data on the neocortex," says Ajay Royyuru, Ph.D., senior manager, Computational Biology Center, IBM research. "We think we can take the strength of the work he and his team have already done and begin to tackle this problem."
 
Early work will attempt to create computer-based simulations of brain function at the molecular level and will build to include simulations of what Royyuru calls "mini columns" small pieces of the neocortex containing anywhere from tens of thousands to hundreds of thousands neurons.
 
"Modeling the brain at the cellular level is a massive undertaking because of the hundreds of thousands of parmaters that need to be taken into account," says Markram in an IBM-issued release announcing the research project. "IBM has unparalleled experience in biological simulations and the most advanced supercomputing technology in the world. With our combined resources and expertise we are embarking on one of the most ambitious research initiatives ever undertaken in the field of neuroscience."
 
In Markram's case, the computing power will greatly accelerate his research since he can run experiments in real time. "With an accurate computer-based model of the brain, much of the pre-testing and planning normally required for a major experiment can be done in silico, rather than in the laboratory," says Markram. "With certain simulations we anticipate that a full day's worth of wet lab research could be done in a matter of seconds on Blue Gene."
 
For IBM, this is exactly the kind of research hoped for back in the blue-sky days of the late 1990s when the project to create Blue Gene began, Royyuru notes. The continuing success of the company's computational biology center depends on being at the forefront of computational biology with projects like Blue Brain. But there may be other benefits down the road, as well.
 
"Biology has a lot to teach us," Royyuru says. "Biology has 4 billion years of learning and it has learned a lot of fancy tricks to harness complexity in such beautiful ways. There are things that we ought to be able to learn by just watching these biological systems and we sincerely hope we might learn what some of those tricks are that can be brought back into man-made systems."

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