Neuromorphic on Fabrizio Ottati

Bits of Chips | TrueNorth

Sun, 26 Mar 2023 00:00:00 +0000

Why do we want to emulate the brain?

If you have ever read an article on neuromorphic computing, you might have noticed that in the introduction of each of these there is the same statement: “The brain is much powerful than any AI machine when it comes to cognitive tasks but it runs on a 10W power budget!”. This is absolutely true: neurons in the brain communicate among each other by means of spikes, which are short voltage pulses that propagate from one neuron to the other. The average spiking activity is estimated to be around 10Hz (i.e. a spike every 100ms). This yields very low processing power consumption, since the activity in the brain results to be really sparse (at least, this is the hypothesis).

Spiking neurons: a digital hardware implementation

Tue, 03 Jan 2023 00:00:00 +0000

In this article, we will try to model a layer of Leaky Integrate and Fire (LIF) spiking neurons using digital hardware: registers, memories, adders and so on. To do so, we will consider a single output neuron connected to multiple input neurons from a previous layer.

In a Spiking Neural Network (SNN), neurons communicate by means of spikes: these activation voltages are then converted to currents through the synapses, charging the membrane potential of the destination neuron. In the following, the destination neuron is denoted as post-synaptic neuron, with the index $i$, while the input neuron under consideration is denoted as pre-synaptic neuron, with the index $j$.