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@(@\newcommand{\W}[1]{ \; #1 \; } \newcommand{\R}[1]{ {\rm #1} } \newcommand{\B}[1]{ {\bf #1} } \newcommand{\D}[2]{ \frac{\partial #1}{\partial #2} } \newcommand{\DD}[3]{ \frac{\partial^2 #1}{\partial #2 \partial #3} } \newcommand{\Dpow}[2]{ \frac{\partial^{#1}}{\partial {#2}^{#1}} } \newcommand{\dpow}[2]{ \frac{ {\rm d}^{#1}}{{\rm d}\, {#2}^{#1}} }@)@This is cppad-20221105 documentation. Here is a link to its current documentation .
Multi-Threaded atomic_two Worker

Purpose
This routine does the computation for one thread.

Source 

namespace {
void multi_atomic_two_worker(void)
{   size_t thread_num  = thread_alloc::thread_num();
    size_t num_threads = std::max(num_threads_, size_t(1));
    bool   ok          = thread_num < num_threads;
    //
    vector<double> x(1), y(1);
    size_t n = work_all_[thread_num]->y_squared->size();
    work_all_[thread_num]->square_root->resize(n);
    for(size_t i = 0; i < n; i++)
    {   x[0] = (* work_all_[thread_num]->y_squared )[i];
        y    = work_all_[thread_num]->fun->Forward(0, x);
        //
        (* work_all_[thread_num]->square_root )[i] = y[0];
    }
    work_all_[thread_num]->ok             = ok;
}
}
Input File: example/multi_thread/multi_atomic_two.cpp