Hi all,

I have a partial differential equation to solve using finite difference. I am trying to understand if it is better to use a vectorized version or a loop version to calculate the right hand side of the equation, which has the spatial discretization. What I am struggling to understand is that for a given grid size (e.g. number of points at which the RHS is evaluated) the vector version performs more poorly than the loop version.

However if I increase the grid size the difference in performance between the two seems to become less.

In order to improve my understanding if Julia performs better with loop or vectorized code I wrote the following code

```
function vect_sum(A,B)
C .= A + B;
return C
end
function loop_sum(A,B,C,m,n)
for i=1:m
for j=1:n
C[i,j] = A[i,j] + B[i,j]
end
end
return C
end
n= 1000
m = 1000
A = rand(m,n)
B = rand(m,n)
C= zeros(m,n);
@btime vect_sum(A,B);
C= zeros(m,n);
@btime loop_sum(A,B,C,m,n);
```

Here, despite the common sense that loop in Julia are faster, I am getting that the vector version of the code perform better than the loop.

Does anybody have an hint on why this is happening?

Thanks