I have a question, what does it mean to find the big-o order of the memory required by an algorithm?

Like what's the difference between that and the big o operations?

E.g

a question asks Given the following pseudo-code, with an initialized two dimensional array A, with both dimensions of size n:

for  i <- 1  to  n  do
       for  j <- 1  to  n-i  do
                        A[i][j]=  i + j

Wouldn't the big o notation for memory just be n^2 and the computations also be n^2?

big-o
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