MATLAB: Spmd running multiple times

neural networksparallel computing

I'm running 2 RBF networks with different spread constant values. I'm trying to use spmd to get both executed in concurrent fashion. Following is the code:
 spread1=365;
 spread2=575;
 goal=0.0;
 max_neurons=2500;
 neuron_jump=500;
 tic
   spmd(2)
     RB_SC_365=newrb(input_mat, targets, goal, spread1, max_neurons, neuron_jump);
     RB_SC_575=newrb(input_mat, targets, goal, spread2, max_neurons, neuron_jump);
   end
 toc
Per my understanding of spmd, spmd(2) will take 2 worker threads from the pool, one will execute RB_SC_365 and other will execute RB_SC_575, and then the script will exit. However, the script is being executed twice.
Here is the output I'm getting:
Lab 1: 
  NEWRB, neurons = 0, MSE = 0.16
Lab 2: 
  NEWRB, neurons = 0, MSE = 0.16
  NEWRB, neurons = 500, MSE = 1.14309e-28
Lab 1: 
  NEWRB, neurons = 500, MSE = 1.14309e-28
Lab 2: 
  NEWRB, neurons = 0, MSE = 0.16
Lab 1: 
  NEWRB, neurons = 0, MSE = 0.16
Lab 2: 
  NEWRB, neurons = 500, MSE = 5.26541e-29
Lab 1: 
  NEWRB, neurons = 500, MSE = 5.26541e-29
As can be seen above, the script has executed twice. The output that I expect is:
Lab 1: 
  NEWRB, neurons = 0, MSE = 0.16
Lab 2: 
  NEWRB, neurons = 0, MSE = 0.16
  NEWRB, neurons = 500, MSE = 1.14309e-28
Lab 1: 
  NEWRB, neurons = 500, MSE = 1.14309e-28
Is there some way to execute the script only once with spmd?

Best Answer

You wrote,
         spmd(2)
     RB_SC_365=newrb(input_mat, targets, goal, spread1, max_neurons, neuron_jump);
     RB_SC_575=newrb(input_mat, targets, goal, spread2, max_neurons, neuron_jump);
   end
"Per my understanding of spmd, spmd(2) will take 2 worker threads from the pool, one will execute RB_SC_365 and other will execute RB_SC_575"
No, that is not correct. All workers will execute what you have inside the spmd directive. You would need to do
         spmd(2)
           if labindex == 1
     RB_SC_365=newrb(input_mat, targets, goal, spread1, max_neurons, neuron_jump);
           else
     RB_SC_575=newrb(input_mat, targets, goal, spread2, max_neurons, neuron_jump);
           end
   end
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