[julia-users] SharedArray / parallel question

[Christopher Alexander]

Hello all, I have a question about the proper usage of SharedArray / 
@parallel.  I am trying to use it in a particular part of my code, but I am 
not getting the expected results (instead I am getting an array of zeros 
each time).

Here are the two functions that are involved:
function partial_rollback!(lattice::TreeLattice, asset::DiscretizedAsset, 
t::Float64)
  from = asset.common.time

  if QuantJulia.Math.is_close(from, t)
    return
  end

  iFrom = findfirst(lattice.tg.times .>= from)
  iTo = findfirst(lattice.tg.times .>= t)

  @simd for i = iFrom-1:-1:iTo
    newVals = step_back(lattice, i, asset.common.values)
    @inbounds asset.common.time = lattice.tg.times[i]
    asset.common.values = sdata(newVals)
    
    if i != iTo
      adjust_values!(asset)
    end
  end

  return asset
end

function step_back(lattice::TreeLattice, i::Int, vals::Vector{Float64})

  newVals = SharedArray(Float64, get_size(lattice.impl, i))
  @parallel for j = 1:length(newVals)
    val = 0.0
    for l = 1:lattice.n
      val += probability(lattice.impl, i, j, l) * 
vals[descendant(lattice.impl, i, j, l)]
    end
    val *= discount(lattice.impl, i, j)
    newVals[j] = val
  end
  retArray = sdata(newVals)
  
  return retArray
end

Is that to much complexity in the parallel loop?  Right now the max # of 
times I've seen over this loop is in the 9000+ range, so that's why I 
thought it would be better than pmap.
Any suggestions?

Thanks!

Chris