And it required 82,944 processors, to do it β€” showing that we're still quite a ways off from being able to match the computational power of the human brain.

Top image: Japan's K Computer β€” a massive array consisting of over 80,000 nodes and capable of 10 petaflops (about 1016 billion operations per second). The system requires 9.89 MW of power to function, the equivalent of 10,000 suburban homes. Credit: RIKEN.


The simulation, which is now considered the largest general neuronal network simulation to date, was performed by a team of Japanese and German researchers on the K Computer β€” a Japanese machine that only two years ago ranked as the world's fastest.

According to the researchers, it took the 82,944 processors about 40 minutes to simulate one second of neuronal network activity in real, biological time. And to make it work, some 1.73 billion virtual nerve cells were connected to 10.4 trillion virtual synapses.

Each virtual synapse, which was positioned between excitatory neurons, contained 24 bytes of memory, thus allowing for an accurate mathematical description of the network. The simulation itself was run on open-source NEST software and had about one petabyte of main memory β€” which is equal to the memory of 250,000 desktop PCs.


The simulation wasn't designed to emulate actual brain activity (the synapses were connected at random) β€” just its network power. And though massive in scale, the simulated network only represented 1% of the neuronal network in the brain.

β€œIf peta-scale computers like the K computer are capable of representing 1% of the network of a human brain today, then we know that simulating the whole brain at the level of the individual nerve cell and its synapses will be possible with exa-scale computers hopefully available within the next decade,” explained Markus Diesmann through a RIKEN release.


Not sure how he can make such a grandiose claim given that this machine β€” as impressive as it is β€” required 40 minutes to just crunch a second's worth of raw brain processing power. And that it represented only 1% the brain's entire network (could you imagine an array 99 times larger than the one featured above!? Though to be sure, Moore's Law will have something to say about the physical size of such arrays by the end of the 2020s.).

Regardless, the researchers say the result will pave the way for combined simulations of the brain and the musculoskeletal system using the K computer. They're obviously hoping that scientists working on various brain mapping initiatives will latch on to their technology.


Needless to say, matching the computational power of the human brain is one thing; emulating it is something entirely different. Due to its complexity, the human brain likely won't be emulated by a computer until sometime after the 2050s.