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CTO describes BrainChip's neural network architecture

18 Dec 2015  | Peter Clarke

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"The SNAP64 architecture is designed to access 65536 (64k) neurons within the same chip, and chips can be stacked to a total of 256B neurons. SNAP64 is fully configurable; the neurotransmitter type and level, neuro-modulators, synaptic connections, and neuron type can be configured through a microprocessor interface. Alternatively, these parameters can be set in the RTL for a dedicated design," wrote van der Made.

Van der Made also provided information on the resolution of potentials in the various parts of the neural network: "Synapses are at this time 18bits wide, but there can be thousands of synapses contributing to the membrane potential of the neuron. The integrator in the dendrites is 22bits wide, and the soma integrator is 24bits wide. These component widths are easily configurable in the RTL if we need more or less resolution."

Finally he pointed out that it is necessary to communicate with the world external to the SNAP64. "To communicate with a computer we need labelled data. For that purpose we have incorporated sensory neurons that take values in and output spikes, and motor neurons that take spikes in and output values."

Applications for the SNAP64 technology include speech- and speaker-recognition, visual and image recognition, robotics, drones and automotive systems. BrainChip said on its website that it is focused on a set of applications that have been prioritised after consultation with potential partners in California. These applications are in the areas of smartphones, Internet of Things and robotics.


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