The largest spiking neural network simulation performed to date modeled the behavior of a network of 1.8 billion neurons, for one second or real time, using the 83,000 processing nodes of the K computer. The simulation took 40 minutes of wall-clock time, using an average number of sinapses, per neuron, of 6000.
This result, obtained by a team of researchers from the Jülich Research Centre and the Riken Advanced Institute for Computational Science, among other institutions, shows that it is possible to simulate networks with more than one billion neurons in fast supercomputers. Furthermore, the authors have shown that the technology scales up and can be used to simulate even larger networks of neurons, perhaps as large as a whole brain.
The simulations were performed using the NEST software package, designed to efficiently model and simulate networks of spiking neurons. If one extrapolates the use of this technology to perform whole brain (with its 88 billion neurons) emulation, the simulation performed using the K super-computer would be about 100,000 times slower than real time.
The K-computer has an estimated performance of 8 petaflops, or 8 quadrillion (10 to the 15th power) floating point operations per second and is currently the world’s fourth fastest computer.