Amit Murthy

If you are building 0.4 from source, could you try with branch https://github.com/JuliaLang/julia/tree/amitm/backport_finalizeshmem ? With the initial code and a `finalize(x)` in the outer loop. In my test the memory...

I think it is apparent that the problem is being caused by `gc` not freeing resources quickly enough. Changed the title to reflect the same.

`interrupt` sends a SIGINT to all the workers. Currently sending a `kill -2` to a running Julia process terminates it. This was not the way SIGINT was handled before. When...

Do you see the same error with ``` S = SharedArray(Int, (3,4), init = S -> S[localindexes(S)] = myid(), pids=remotes) r = @spawnat remotes[1] S*eye(4) fetch(r) ```

The previous invocation, while a bit inefficient should have worked too. And we could do a better job of "show" on unmapped workers.

The reason for the undefined ref error in your case was because `S` in the invocation of `S*eye(4)` on worker 3 was actually the one constructed on pids 1 and...

This is by design. You need to execute computation on the host where the shmem is mapped else we would just be pulling the entire array over the network. Shared...

It didn't exist. See my comment above - https://github.com/JuliaLang/Distributed.jl/issues/32

The two open issues are related to treatment of module globals and module loading on workers. The main reported issue i.e., scoping w.r.t. parallel macros has been largely addressed by...

Some progress: ``` addprocs(2) rr = RemoteRef(2) put!(rr, :OK) Base.remote_do(3, x->nothing, rr) rr=nothing @everywhere gc() @everywhere gc() Base.remote_do(2, ()->println(Base.PGRP.refs[(1,4)].clientset)) # Execute a dummy remote_do again. This collects the previous ref...