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Scientists at IBM Research have created by far the most advanced neuromorphic (brain-like) computer chip to date. The chip, called TrueNorth, consists of 1 million programmable neurons and 256 million programmable synapses across 4096 individual neurosynaptic cores. Built on Samsung’s 28nm process and with a monstrous transistor count of 5.4 billion, this is one of the largest and most advanced computer chips ever made. Perhaps most importantly, though, TrueNorth is incredibly efficient: The chip consumes just 72 milliwatts at max load, which equates to around 400 billion synaptic operations per second per watt — or about 176,000 times more efficient than a modern CPU running the same brain-like workload, or 769 times more efficient than other state-of-the-art neuromorphic approaches. Yes, IBM is now a big step closer to building a brain on a chip.
The animal brain (which includes the human brain, of course), as you may have heard before, is by far the most efficient computer in the known universe. As you can see in the graph below, the human brain has a “clock speed” (neuron firing speed) measured in tens of hertz, and a total power consumption of around 20 watts. A modern silicon chip, despite having features that are almost on the same tiny scale as biological neurons and synapses, can consume thousands or millions times more energy to perform the same task as a human brain. As we move towards more advanced areas of computing, such as artificial general intelligence and big data analysis — areas that IBM just happens to be deeply involved with — it would really help if we had a silicon chip that was capable of brain-like efficiency.
Each TrueNorth chip consists of 4096 neurosynaptic cores arranged in a 64×64 grid. Each core is self-contained, with 256 inputs (axons), 256 outputs (neurons), a big bank of SRAM (which stores the data for each neuron), and a router that allows for any neuron to transmit to any axon up to 255 cores away. Information flows across TrueNorth by way of neural spikes, from axons to neurons, modulated by the programmable synapses between them. This architecture is fundamentally based on Cornell Tech’s original work on asynchronous circuit design, which IBM has been refining since 2008. You would definitely call this a non-Von Neumann chip design.
At this point, it’s worth noting that TrueNorth is pretty much ready to go for commercial applications. On the data center/supercomputer side of things, IBM already has dozens of big data solutions — such as Watson — that could be dramatically enhanced by TrueNorth. For consumers, the fact that TrueNorth consumes much less power than conventional Von Neumann chips could be significant. While TrueNorth isn’t going to run your operating system any time soon, it would make a fantastically efficient coprocessor to handle sensor input, computer vision, AI (self-driving cars), and other emerging spheres in personal/wearable computing.
Neural networks are fantastic things, but historically they operate on hugely inefficient clusters of conventional computers. With TrueNorth’s truly novel architecture, that changes — with TrueNorth, IBM is now a big step closer to building a brain on a chip, and that could be big news for the future of computing.
IBM cracks open a new era of computing with brain-like chip: 4096 cores, 1 million neurons, 5.4 billion transistors | ExtremeTech
The animal brain (which includes the human brain, of course), as you may have heard before, is by far the most efficient computer in the known universe. As you can see in the graph below, the human brain has a “clock speed” (neuron firing speed) measured in tens of hertz, and a total power consumption of around 20 watts. A modern silicon chip, despite having features that are almost on the same tiny scale as biological neurons and synapses, can consume thousands or millions times more energy to perform the same task as a human brain. As we move towards more advanced areas of computing, such as artificial general intelligence and big data analysis — areas that IBM just happens to be deeply involved with — it would really help if we had a silicon chip that was capable of brain-like efficiency.
Each TrueNorth chip consists of 4096 neurosynaptic cores arranged in a 64×64 grid. Each core is self-contained, with 256 inputs (axons), 256 outputs (neurons), a big bank of SRAM (which stores the data for each neuron), and a router that allows for any neuron to transmit to any axon up to 255 cores away. Information flows across TrueNorth by way of neural spikes, from axons to neurons, modulated by the programmable synapses between them. This architecture is fundamentally based on Cornell Tech’s original work on asynchronous circuit design, which IBM has been refining since 2008. You would definitely call this a non-Von Neumann chip design.
At this point, it’s worth noting that TrueNorth is pretty much ready to go for commercial applications. On the data center/supercomputer side of things, IBM already has dozens of big data solutions — such as Watson — that could be dramatically enhanced by TrueNorth. For consumers, the fact that TrueNorth consumes much less power than conventional Von Neumann chips could be significant. While TrueNorth isn’t going to run your operating system any time soon, it would make a fantastically efficient coprocessor to handle sensor input, computer vision, AI (self-driving cars), and other emerging spheres in personal/wearable computing.
Neural networks are fantastic things, but historically they operate on hugely inefficient clusters of conventional computers. With TrueNorth’s truly novel architecture, that changes — with TrueNorth, IBM is now a big step closer to building a brain on a chip, and that could be big news for the future of computing.
IBM cracks open a new era of computing with brain-like chip: 4096 cores, 1 million neurons, 5.4 billion transistors | ExtremeTech
