I'm trying to use parallelism in julia for a task with a structure that I
think is quite pervasive. It looks like this:
# broadcast lists of functions f and g to all processes so they're
available everywhere
# create shared arrays X,Y on all processes so they're available everywhere
for iteration=1:1000
@parallel for i=1:size(X)
X[i] = f[i](Y)
end
@parallel for j=1:size(Y)
Y[j] = g[j](X)
end
end
I'm having trouble making this work, and I'm not sure where to dig around
to find a solution. Here are the difficulties I've encountered:
* @parallel doesn't allow me to create persistent variables on each
process; ie, the following results in an error.
s = Base.shmem_rand(12,3)
@parallel for i=1:nprocs() m,n = size(s) end
@parallel for i=1:nprocs() println(m) end
* @everywhere does allow me to create persistent variables on each process,
but doesn't send any data at all, including the variables I need in order
to define new variables. Eg the following is an error: s is a shared array,
but the variable (ie pointer to) s is apparently not shared.
s = Base.shmem_rand(12,3)
@everywhere m,n = size(s)
Here are the kinds of questions I'd like to see protocode for:
* How can I broadcast a variable so that it is available and persistent on
every process?
* How can I create a reference to the same shared array "s" that is
accessible from every process?
* How can I send a command to be performed in parallel, specifying which
variables should be sent to the relevant processes and which should be
looked up in the local namespace?
Note that everything I ask above is not specific to shared arrays; the same
constructs would also be extremely useful in the distributed case.
----------------------
An interesting partial solution is the following:
funcs! = Function[x->x[:] = x+k for k=1:3]
d = drand(3,12)
let funcs! = funcs!
@sync @parallel for k in 1:3
funcs)
end
end
Here, I'm not sure why the let statement is necessary to send funcs!, since
d is sent automatically.
---------------------
Thanks!
Madeleine
