> > Suppose we have a vector of futures of type T and we want to reduce the
> > values contained in the futures using T op(T, T), with initial value of
> > init. What is the HPX recommended way of doing this? What should the
> > implementation of "future<T> myreduce(vector<future<T> > fs, T init, Op
> > op)" be?
> >
> > hpx::parallel::reduce can't be used with a vector of futures.
> > hpx::lcos::reduce isn't what we're looking for as this isn't a distributed
> > operation. One option is to use hpx::when_any and accumulate the values as
> > they are ready. But this serializes the accumulation of the futures, which
> > may not be desirable.
>
> How about:
>
> vector<future<T>> v = ...;
> future<T> f =
> dataflow(unwrapped(
> [](vector<T> && data) -> T
> {
> return parallel::reduce(
> par, data.begin(), data.end(), op);
> }),
> std::move(v)
> );
This would work but wouldn't parallel::reduce not start until all
of the futures in v are ready? I'd be concerned that waiting on all of v
could take too long. Especially if this were the last task in an
application (no other asynchrony is available) and some elements in v
may be ready much later than other elements in v.
Thanks,
Daniel
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