SharedArray not working on remote machines

I am trying to set up SharedArrays on remote machines. I.e. shared among processes on the same machine. Unfortunately this doesn't seem to work. I am using version 0.5.0-dev+749 of julia.

julia> addprocs(1) #add one process on the master node
1-element Array{Int64,1}:
 2

julia> println(procs())
[1,2]

julia> S = SharedArray(Int, (3,4), init = S -> S[localindexes(S)] = myid(), pids=Int[1,2])
3x4 SharedArray{Int64,2}:
 1  1  2  2
 1  1  2  2
 1  1  2  2

julia> using ClusterManagers

julia> remotes = addprocs(SlurmManager(2), nodes=1)
srun: job 1828134 queued and waiting for resources
srun: job 1828134 has been allocated resources
2-element Array{Int64,1}:t of 2
 3
 4

julia> for w in remotes #both remote processes are on the same machine
           println(remotecall_fetch(readall, w, `hostname`)) 
       end
mrc-bsu-tesla1

mrc-bsu-tesla1


julia> r = @spawnat remotes[1] S = SharedArray(Int, (3,4), init = S -> S[localindexes(S)] = myid(), pids=remotes)
RemoteRef{Channel{Any}}(3,1,14)

julia> fetch(r)
3x4 SharedArray{Int64,2}:
 #undef  #undef  #undef  #undef
 #undef  #undef  #undef  #undef
 #undef  #undef  #undef  #undef

julia> r = @spawnat remotes[1] S*eye(4) #convert to regular array
RemoteRef{Channel{Any}}(3,1,16)

julia> fetch(r)
ERROR: On worker 3:
UndefRefError: access to undefined reference
 [inlined code] from sharedarray.jl:294
 in copy_transpose! at abstractarray.jl:513
 in copy_transpose! at linalg/matmul.jl:349
 in generic_matmatmul! at linalg/matmul.jl:459
 in * at linalg/matmul.jl:144
 in anonymous at multi.jl:1330
 in anonymous at multi.jl:889
 in run_work_thunk at multi.jl:645
 in run_work_thunk at multi.jl:654
 in anonymous at task.jl:54
 in remotecall_fetch at multi.jl:731
 [inlined code] from multi.jl:368
 in call_on_owner at multi.jl:776
 in fetch at multi.jl:784

Reproduce the remote SharedArray setup with ClusterManagers and two processes on the same machine. Start at sharedarray.jl:294 and inspect the failing access shown in the stack trace. Done means SharedArray initialization and subsequent operations work for remote processes on the same machine without undefined references.