Question

I am presently using openMP for the first time, and have hit my head against the “data members cannot be private”-rule.

I would like to know whether the below is valid, or if it will eventually break:

class network
{
    double tau;
    void SomeFunction();
};

void network::SomeFunction()
{
    #pragma omp parallel for // <-the openMP call
    for (uint iNeu=0;iNeu<nNeurons;++iNeu)
    {
        neurons[iNeu].timeSinceSpike+=tau;  //tau is defined in some other place
        neurons[iNeu].E+=tau*tau;
    }   
}

So, I am using the minimal syntax, and letting openMP figure out everything on its own. This version compiles, and the output is correct (so far).
What I tried before that was

void network::SomeFunction()
{
    #pragma omp parallel for default(none) shared(neurons) firstprivate(tau)  // <-the openMP call
    for (uint iNeu=0;iNeu<nNeurons;++iNeu)
    {
        neurons[iNeu].timeSinceSpike+=tau; //tau is defined in some other place
        neurons[iNeu].E+=tau*tau;
    }   
}

However, as hinted, that won’t compile, presumably because tau and neurons are data members of network.

The question then is, if I have really just been lucky in my runs of the first version, and whether I have to do something like

void network::SomeFunction()
{
    double tempTau=tau;
    vector <neuron> tempNeurons=neurons; //in realtity this copy-process would be quite involved
    #pragma omp parallel for shared(tempNeurons) firstprivate(tempTau)// <-the openMP call
    for (uint iNeu=0;iNeu<nNeurons;++iNeu)
    {
        tempNeurons[iNeu].timeSinceSpike+=tempTau;
        tempNeurons[iNeu].E+=tempTau*tempTau;
    }   
}

Naturally, I would much prefer to stick with the present version, as it is so short and easy to read, but I would also like to trust my output 🙂
I am using gcc 4.6.1

Hope someone can educate me on the proper way to do it.

Answer 1

In this example, what you are initially doing should be fine:

• The reason is that you aren’t modifying the tau member at all. So there’s no reason to make it private in the first place. It’s safe to asynchronously share the same value if it isn’t modified.
• As for neurons, you are modifying the elements independently. So there’s no problem here either.

When you declare a variable as firstprivate, it gets copy constructed into all the threads. So shared(tempNeurons) is definitely not what you want to do.