You can put a type assertion on any expression to guarantee its type in a
way that type inference will understand. E.g.
v = fetch(rr)::Vector{Float64}
n = dict[key]::Int
This will emit a run-time type check on the result, but after that, the
type of the value is known and efficient code will be emitted.
On Mon, May 11, 2015 at 10:26 AM, Tom Lee <[email protected]> wrote:
> Hello All,
>
> I am looking into the possibility of writing a parallel molecular dynamics
> code in Julia with a domain decomposition algorithm along the lines of
> LAMMPS <http://lammps.sandia.gov/>. So far I am just writing a serial
> version, but I am trying to think ahead towards parallelization.
>
> Something troubles me regarding type stability in parallel code - it seems
> that a call to fetch(remoteref) could return potentially any type, so that
> the compiler cannot assume a function containing fetch will be type stable.
> Is there a way to tell julia what type will be returned, or do we just have
> to live with the slowdown? This may be an issue for algorithms like
> molecular dynamics that require communication every timestep.
>
> Surely it would at least be technically possible for fetch to be
> type-stable if remotecall could be given some advance information about the
> type which will be returned, but as far as I can tell nothing like this is
> implemented.
>
> Cheers,
>
> Tom
>
