$\newcommand{\W}[1]{ \; #1 \; } \newcommand{\R}[1]{ {\rm #1} } \newcommand{\B}[1]{ {\bf #1} } \newcommand{\D}[2]{ \frac{\partial #1}{\partial #2} } \newcommand{\DD}[3]{ \frac{\partial^2 #1}{\partial #2 \partial #3} } \newcommand{\Dpow}[2]{ \frac{\partial^{#1}}{\partial {#2}^{#1}} } \newcommand{\dpow}[2]{ \frac{ {\rm d}^{#1}}{{\rm d}\, {#2}^{#1}} }$

Syntax
ok = multi_atomic_run(y_squared, square_root)

It is assumed that this function is called by thread zero and all the other threads are blocked (waiting).

y_squared
This argument has prototype       const vector<double>& y_squared  and its size is equal to the number of threads. It is the values that we are computing the square root of.

square_root
This argument has prototype       vector<double>& square_root  The input value of square_root does not matter. Upon return, it has the same size and is the element by element square root of y_squared .

ok
This return value has prototype       bool ok  If it is false, multi_atomic_run detected an error.

Source

namespace {
bool multi_atomic_run(
const vector<double>& y_squared  ,
vector<double>&      square_root )
{
bool ok = true;

// setup the work for multi-threading
ok &= multi_atomic_setup(y_squared);

// now do the work for each thread
}