BrainChip provides details of neural network architecture

December 15, 2015 // By Peter Clarke
Peter van der Made, CTO and interim CEO of BrainChip Inc. (Aliso Viejo, Calif.) has provided more details of his company's spiking neural network architecture, SNAP64.

The company's business model was discussed by last month (Startup wants to be the ARM of neuromorphic cores). The company's technology is known as SNAP standing for Spiking Neuron Adaptive Processor.
 

One of the main differences between BrainChip's implementations and some other neuromorphic processors implemented in both hardware and software is that Peter van der Made has attempted a closer modelling of biological neural networks; including the spike train method of data transfer and modelling of multiple modulations of signals at the synaptic connection.

"The number of neurons and synapses is configurable in the RTL. We could put as many as 10,000 neurons and 5 million synapses on a single die. These are neurons that behave like biological neurons with multiple spiking modes and dynamic, temporal integrating synapses," said Van der Made in email communication with EE Times Europe. He added: "The neurons and synapses are not multiplexed – unlike other designs like IBM's TrueNorth which are multiplexed 256x and do not learn."

Peter van der Made, CTO and interim CEO of BrainChip Inc.

 

"The advantage of not multiplexing is that they are thousands of times faster, that all memory can be distributed, which simplifies the learning method. The learning method we use is STDP – Spike Time Dependent Plasticity, which constantly accesses memory," said Van der Made.

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