### Inverting matrix after Cholesky decomposition does not finish for "large" dimension

I'm trying to invert the cholesky decomposition of a matrix. While this works for small a, for around a=~30, it no longer finishes.

From the _print_, I know that the problem is in the last line.

This seems a very odd behavior, as like matrix inversion would blow exponentially, which is not true, but even if it was it shouldn't go from taking 10s to finish to not finishing at all. Moreover, since the matrix N is triangular, shouldn't it even be faster to compute the inverse matrix?

I am very puzzled about this, sorry...

```
a = 30
M = random_matrix(ZZ, a, x = -a, y = a)
M = M.T * M
N = M.inverse().cholesky()
print "choleskied"
Ni = N.inverse()
```

Thanks for the help!