What is neuromorphic computing? Everything you need to know about how it is changing the future of computing. By Jo Best.
Neuromorphic computing could completely transform everything about the technology industry from programming languages to hardware. As the name suggests, neuromorphic computing uses a model that’s inspired by the workings of the brain. The brain makes a really appealing model for computing: unlike most supercomputers, which fill rooms, the brain is compact, fitting neatly in something the size of, well… your head.
Brains also need far less energy than most supercomputers: your brain uses about 20 watts, whereas the Fugaku supercomputer needs 28 megawatts – or to put it another way, a brain needs about 0.00007% of Fugaku’s power supply.
The article tries to answer following questions:
- Why do we need neuromorphic systems?
- So how can you make a computer that works like the human brain?
- What uses could neuromorphic systems be put to?
- Are there neuromorphic computer systems available today?
- What are the challenges to using neuromorphic systems?
- Do we know enough about the brain to start making brain-like computers?
Most hardware today is based on the von Neumann architecture, which separates out memory and computing. Because von Neumann chips have to shuttle information back and forth between the memory and CPU, they waste time (computations are held back by the speed of the bus between the compute and memory) and energy – a problem known as the von Neumann bottleneck.
For compute heavy tasks, edge devices like smartphones currently have to hand off processing to a cloud-based system, which processes the query and feeds the answer back to the device. With neuromorphic systems, that query wouldn’t have to be shunted back and forth, it could be conducted within the device itself. Good read!
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