neuron.v

/*
In genereal the activation function is:
             -----
             \
              \  (w_i*x_i)+bias
f(w_i,x_i) =  /
             /____

when f(w,x) > 0, then the output spikes

*/
module neuron #(
    parameter NUMBER_SYNAPSES = 8,
    parameter NUMBER_RNN_SYNAPSES = 8
)
(
    clk,
    rst,
    // Turn on processing
    run_inference,
    inference_done,
    // The layer i/o
    rnn_inputs,
    neuron_inputs,
    neuron_output,
    // Backprop
    backprop_enable,
    backprop_out_port,
    backprop_in_port,
    backprop_done,
    // Data interface
    read_enable,
    write_enable,
    read_done,
    write_done,
    address,
    data_i,
    data_o
);
    parameter NUM_WEIGHTS = NUMBER_SYNAPSES+NUMBER_RNN_SYNAPSES;

    input clk;
    input rst;
    input run_inference;
    output reg inference_done;
    input[NUMBER_SYNAPSES-1:0] neuron_inputs;
    input[NUMBER_RNN_SYNAPSES-1:0] rnn_inputs;
    output reg neuron_output;

    output reg write_done;
    output reg read_done;

    // Data interface
    input write_enable;
    input read_enable;
    input [$clog2(NUMBER_SYNAPSES+NUMBER_RNN_SYNAPSES+2):0] address;
    input [31:0] data_i;
    output reg [31:0] data_o;

    // Backprop
    output reg [NUMBER_SYNAPSES-1:0] backprop_out_port; // tell the other neurons that they have to better themselves
    input [NUMBER_SYNAPSES-1:0] backprop_in_port; // Constructive criticism for the neuron
    output reg backprop_done;
    input backprop_enable;
    reg backprop_running;

    reg signed[NUMBER_SYNAPSES-1:0][31:0] W; // summands
    reg signed[NUMBER_RNN_SYNAPSES-1:0][31:0] RNNW; // RNN summands
    reg signed[31:0] bias; // summands
    reg signed[31:0] dw; // weight correction