I mirror here my question at StackOverflow: How to increase stack size for Julia in Windows? - Stack Overflow

I wrote a recursive function (basically a flood fill), it works fine on smaller datasets, but for slightly larger input it throws `StackOverflowError`

.

How to increase the stack size for Julia under Windows 10? Ideally the solution should be applicable to JupyterLab.

It’s a singe use program, no point in optimizing/rewriting it, I just need to peak at the result and forget about the code.

As a test case, I provide the following MWE. This is just a simple algorithm that recursively visits each cell of `n`

by `n`

array:

```
n = 120
visited = fill(false, (n,n))
function visit_single_neighbour(i,j,Δi,Δj)
if 1 ≤ i + Δi ≤ n && 1 ≤ j + Δj ≤ n
if !visited[i+Δi, j+Δj]
visited[i+Δi, j+Δj] = true
visit_four_neighbours(i+Δi, j+Δj)
end
end
end
function visit_four_neighbours(i,j)
visit_single_neighbour(i,j,1,0)
visit_single_neighbour(i,j,0,1)
visit_single_neighbour(i,j,-1,0)
visit_single_neighbour(i,j,0,-1)
end
@time visit_four_neighbours(1,1)
```

For `n = 120`

the output is `0.003341 seconds`

, but for `n = 121`

it throws `StackOverflowError`

.

On a Linux machine with `ulimit -s unlimited`

the code runs no problem for `n = 2000`

and takes about 2.4 seconds.