Large number of temporary shared arrays crashes Julia. Need a more aggressive gc?

On my computer julia always crashes on this code:

@everywhere const m     = 100
@everywhere const n     = 100
@everywhere const T     = 100

@everywhere @inline function slice!(x, t, p)
    #   do something
end

function shared_test(p)
    x   = SharedArray(Float64, (m, n, T), init= S -> S[localindexes(S)] = 0.0)

    @sync @parallel for t= 1:T
        slice!(x, t, p)
    end
    return x
end 

function doit()
    p   = rand(m,n,T)

    for i=1: 10000000000
        x = shared_test(p)
        println(i)
    end
end

doit()

This triggers a signal (7): Bus error which results in the workers beeing killed.

I tested this, because I wanted to isolate a memory leak that I suspect. I think it also occurs here, but Julia crashes before I can tell.

I think, if I leave out the Initialization:

x   = SharedArray(Float64, (m, n, T), init= S -> S[localindexes(S)] = 0.0)

by changing the line to

x   = SharedArray(Float64, (m, n, T))

there is no memory leak, but then there are other errors. I am also not sure if the parallel loop is relevant for this.

versioninfo:

Julia Version 0.4.4-pre+35
Commit 1a9429e (2016-02-12 13:21 UTC)
Platform Info:
  System: Linux (x86_64-pc-linux-gnu)
  CPU: AMD Phenom(tm) II X4 955 Processor
  WORD_SIZE: 64
  BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Barcelona)
  LAPACK: libopenblas64_
  LIBM: libopenlibm
  LLVM: libLLVM-3.3

Start with the shared_test and doit reproducer, focusing on SharedArray creation with the init callback and the @sync @parallel loop. Reproduce the Bus error using the Julia version and platform details provided, then compare behavior without initialization. Done means identifying the cause of the worker crash or memory leak and documenting a verified fix.