Efficient random number generation with C++11

Question

I am trying to understand how the C++11 random number generation features are meant to be used. My concern is performance.

Suppose that we need to generate a series of random integers between 0..k, but k changes at every step. What is the best way to proceed?

Example:

for (int i=0; i < n; ++i) {
    int k = i; // of course this is more complicated in practice
    std::uniform_int_distribution<> dist(0, k);
    int random_number = dist(engine);
    // do something with random number
}

The distributions that the header provides are very convenient. But they are opaque to the user, so I cannot easily predict how they will perform. It is not clear for example how much (if any) runtime overhead will be caused by the construction of dist above.

Instead I could have used something like

std::uniform_real_distribution<> dist(0.0, 1.0);
for (int i=0; i < n; ++i) {
    int k = i; // of course this is more complicated in practice
    int random_number = std::floor( (k+1)*dist(engine) );
    // do something with random number
}

which avoids constructing a new object in each iteration.

Random numbers are often used in numerical simulations where performance is important. What is the best way to use in these situations?

Please do no answer "profile it". Profiling is part of effective optimization, but so is a good understanding of how a library is meant to be used and the performance characteristics of that library. If the answer is that it depends on the standard library implementation, or that the only way to know is to profile it, then I would rather not use the distributions from at all. Instead I can use my own implementation which will be transparent to me and much easier to optimize if/when necessary.

Efficient random number generation with C++11 <random>

2 Answers