How can I implement parallel processing in a C++ ML library?

How can I implement parallel processing in a C++ ML library?

You can use libraries like OpenMP or Intel TBB to implement parallel processing in your C++ ML library. Would you like examples?

Yes, please provide an example using OpenMP.

Sure! Here's a simple example:

#include <omp.h>
#include <vector>

void parallelComputation(std::vector<int>& data) {
    #pragma omp parallel for
    for (int i = 0; i < data.size(); ++i) {
        data[i] = data[i] * 2; // Example operation
    }
}

This code doubles each element in the vector using parallel processing.

What if I want to use Intel TBB instead?

With Intel TBB, you can use the parallel_for function. Here's an example:

#include <tbb/tbb.h>
#include <vector>

void parallelComputation(std::vector<int>& data) {
    tbb::parallel_for(size_t(0), data.size(), [&](size_t i) {
        data[i] = data[i] * 2; // Example operation
    });
}

Are there any performance considerations I should keep in mind?

Yes, consider the overhead of thread management and the size of the data. For small datasets, parallel processing might not yield significant performance gains.