Performance issue in `DArray` creation when `myid()` holds a chunk

Hello,

If the `pid` trying to create a `DArray` has to do enough work, we see a slow down. The work interferes with the asynchronous dispatch of work to the other `pids`.

```julia
using Distributed
addprocs(2)
using DistributedArrays

# a lot of work...
@everywhere function init(I)
rr=rand(map(length,I)...)
ss=0.
for _ in 1:10
ss+=sum(rr.^2)
end
exp.(ss*exp.(rr).^3)
end

n=2000
@btime d1=DArray(init,(n,n),workers()[1:2])
@btime d1=DArray(init,(n,n),procs()[1:2])
@btime d1=DArray(init,(n,n),procs()[2:-1:1]);

126.553 ms (290 allocations: 22.45 KiB)
156.219 ms (253 allocations: 213.64 MiB)
112.563 ms (249 allocations: 213.64 MiB)
```
Note that in the last experiment, the same `pids` are included, but the `pid==1` is last and the slowdown disappears (it dispatches the work to others before doing its own). Which suggests the easy fix:

```julia
@everywhere @eval DistributedArrays function DistributedArrays.DArray(id, init, dims, pids, idxs, cuts)
localtypes = Vector{DataType}(undef,length(pids))

pids=copy(pids)
ind=findfirst(isequal(myid()),pids)
if ind != nothing
pids[end],pids[ind]=pids[ind],pids[end]
end


@sync begin
for i = 1:length(pids)
@async begin
local typA
if isa(init, Function)
typA = remotecall_fetch(construct_localparts, pids[i], init, id, dims, pids, idxs, cuts)
else
# constructing from an array of remote refs.
typA = remotecall_fetch(construct_localparts, pids[i], init[i], id, dims, pids, idxs, cuts)
end
localtypes[i] = typA
end
end
end

if length(unique(localtypes)) != 1
@sync for p in pids
@async remotecall_fetch(release_localpart, p, id)
end
throw(ErrorException("Constructed localparts have different `eltype`: $(localtypes)"))
end
A = first(localtypes)

if myid() in pids
d = registry[id]
d = isa(d, WeakRef) ? d.value : d
else
T = eltype(A)
N = length(dims)
d = DArray{T,N,A}(id, dims, pids, idxs, cuts, empty_localpart(T,N,A))
end
d
end
```

And after the fix:
```julia
@btime d1=DArray(init,(n,n),workers()[1:2])
@btime d1=DArray(init,(n,n),procs()[1:2])
@btime d1=DArray(init,(n,n),procs()[2:-1:1]);

79.150 ms (296 allocations: 22.64 KiB)
111.481 ms (258 allocations: 213.64 MiB)
111.870 ms (258 allocations: 213.64 MiB)
```

Will submit a PR with the fix promptly :)

Cheers!