A supercomputer scheduled to go online in April 2024 will rival the estimated rate of operations in the human brain, according to researchers in Australia. It’s the world’s first supercomputer capable of simulating networks of neurons and synapses at the scale of the human brain.
DeepSouth belongs to an approach known as neuromorphic computing, which aims to mimic the biological processes of the human brain.
Our brain is the most amazing computing machine we know. By distributing its computing power to billions of small units that interact through trillions of connections, the brain can rival the most powerful supercomputers in the world, while requiring only the same power used by a fridge lamp bulb.
Among other things, neuromorphic computing aims to unlock the secrets of this amazing efficiency.
On June 30, 1945, the mathematician and physicist John von Neumann described the design of a new machine, the Electronic Discrete Variable Automatic Computer. This effectively defined the modern electronic computer as we know it. These all have distinct processing and memory units, where data and instructions are stored in the memory and computed by a processor.
This allowed us to have smaller and cheaper computers. To overcome this issue, scientists are exploring new approaches to computing, starting from the powerful computer we all have hidden in our heads, the human brain. Our brains do not work according to John von Neumann’s model of the computer.
They don’t have separate computing and memory areas. The organization of neurons and synapses in the brain is flexible, scalable, and efficient. Since the late 1980s, scientists have been studying this model with the intention of importing it to computing. Neuromorphic computers are based on intricate networks of simple, elementary processors.
Because the computations performed by individual neurons and synapses are very simple compared with traditional computers, the energy consumption is orders of magnitude smaller.
This speeds up the brain’s computing in general because there is no separation between memory and processor, which in classical machines causes a slowdown.
It also avoids the need to perform a specific task of accessing data from a main memory component, as happens in conventional computing systems and consumes a considerable amount of energy. It is worth mentioning the Human Brain Project, funded under an EU initiative.
BrainScaleS can simulate how neurons “Spike,” the way that an electrical impulse travels along a neuron in our brains. Because they are engineered to mimic actual brains, neuromorphic computers could be the beginning of a turning point.
Offering sustainable and affordable computing power and allowing researchers to evaluate models of neurological systems, they are an ideal platform for a range of applications. They have the potential to both advance our understanding of the brain and offer new approaches to artificial intelligence.