This ought to work. The warning is interesting, since the
DataStructures package does (for me at least) define a DataStructures
module. Is it possible DataStructures is not fully installed, missing
files or something like that?
On Wed, Jan 22, 2014 at 1:01 AM, Madeleine Udell
<madeleine.ud...@gmail.com> wrote:
> I'm trying to understand the most Julian way to perform a particular
> parallel programming task. Suppose I need function foo from module.jl to be
> available everywhere. Let's call the following code map_foo.jl:
>
> @everywhere include("module.jl")
> @everywhere using MyModule
> pmap(foo,1:100)
>
> That works fine, except when module.jl itself has other dependencies on
> other modules:
>
> module MyModule
>
> using DataStructures
> export foo
>
> function foo(i)
> return Queue(i)
> end
>
> end # module
>
> In this case, it works to call
>
> julia map_foo.jl
>
> but when I call
>
> julia -p 2 map_foo.jl
>
> I get the following error
>
> Warning: requiring "DataStructures" did not define a corresponding module.
> Warning: requiring "DataStructures" did not define a corresponding module.
> exception on exception on 2: 3: ERROR: ERROR: Queue not definedQueue not
> defined
> in
> in foo at /Users/madeleineudell/Dropbox/pestilli_icme_life
> (1)/src/julia/questions/module.jl:7
> in anonymous at multi.jl:834
> in run_work_thunk at multi.jl:575
> in anonymous at task.jl:834
> foo at /Users/madeleineudell/Dropbox/pestilli_icme_life
> (1)/src/julia/questions/module.jl:7
> in anonymous at multi.jl:834
> in run_work_thunk at multi.jl:575
> in anonymous at task.jl:834
>
> Does anyone know how I can successfully chain dependencies like this when
> using parallelism? Calling @everywhere on the import call in module.jl also
> doesn't fix the problem, strangely enough.
>
> Of course, if I could put all my code into shared memory, I'd be much
> happier. I just saw an update adding shared memory arrays, but I don't know
> if there's a way to get shared memory code!
>
