The most powerful supercomputer simulating the work of the human brain was launched for the first time.
Today, supercomputers are used for a wide range of tasks: from various mathematical calculations and processing of arrays of data to modeling pharmaceutical compounds and the work of artificial intelligence. However, there are computers aimed at the most accurate reproduction of the “architecture” of the human brain. And the most powerful today such neuromorphic supercomputer was recently launched for the first time.
This computer is called Spiking Neural Network Architecture (SpiNNaker) and it can perform more than 200 million operations per second, and each of the microchips has 100 million parts. The machine is assembled on the basis of the School of Computer Science at the University of Manchester and 15 million pounds was spent on this project. But this amount is not as impressive as the time it took to develop: the concept of a supercomputer was studied for 20 years and another 10 years was required for assembly.
SpiNNaker can simulate the behavior of human neurons in real time and is unique in that, unlike traditional computers, it does not transmit large amounts of information from point A to point B, but sends data at one time to thousands of different directions. This is how our brain cells work. As one of the project’s ideologists, computer technology professor Steve Furber, stated
“SpiNNaker completely changes the way computers work. In fact, we created a machine that works more like a brain than a traditional computer, which is extremely interesting. The ultimate goal of our project has always been to use a billion cores in a single computer that simulates the brain and today we have achieved this goal. And this is just fantastic. ”
It is worth noting that even despite the fact that “a real artificial brain” has earned, the number of nuclei that is in it now is simulated by the brain, which is equivalent to 1% of the human. However, already now this neuromorphic supercomputer will help to understand how our central nervous system functions, as well as provide an opportunity to conduct large-scale simulations not available on traditional machines.