I am asking this as the other relevant questions on SO seem to be either for older versions of the C++ standard, do not mention any form of parallelization, or are focused on keeping the ordering/indexing the same as elements are removed.
I have a vector of potentially hundreds of thousands or millions of elements (which are fairly light structures, around ~20 bytes assuming they're compacted down).
Due to other restrictions, it must be a std::vector
and other containers would not work (like std::forward_list
), or be even less optimal in other uses.
I recently swapped from simple it = std::erase(it)
approach to using pop-and-swap using something like this:
for(int i = 0; i < myVec.size();) {
// Do calculations to determine if element must be removed
// ...
// Remove if needed
if(elementMustBeRemoved) {
myVec[i] = myVec.back();
myVec.pop_back();
} else {
i++;
}
}
This works, and was a significant improvement. It cut the runtime of the method down to ~61% of what it was previously. But I would like to improve this further.
Does C++ have a method to remove many non-consecutive elements from a std::vector
efficiently? Like passing a vector of indices to erase()
and have C++ do some magic under the hood to minimize movement of data?
If so, I could have threads individually gather indices that must be removed in parallel, and then combine them and pass them to erase().
Take a look at std::remove_if algorithm. You could use it like this:
auto firstToErase = std::remove_if(myVec.begin(), myVec.end(),
[](const & T x){
// Do calculations to determine if element must be removed
// ...
return elementMustBeRemoved;});
myVec.erase(firstToErase, myVec.end());
cppreference says that following code is a possible implementation for remove_if:
template<class ForwardIt, class UnaryPredicate>
ForwardIt remove_if(ForwardIt first, ForwardIt last, UnaryPredicate p)
{
first = std::find_if(first, last, p);
if (first != last)
for(ForwardIt i = first; ++i != last; )
if (!p(*i))
*first++ = std::move(*i);
return first;
}
Instead of swapping with the last element it continuously moves through a container building up a range of elements which should be erased, until this range is at the very end of vector. This looks like a more cache-friendly solution and you might notice some performance improvement on a very big vector.
If you want to experiment with a parallel version, there is a version (4) which allows to specify execution policy.