$$ \array{ A(0,n) &= & n+1\\ A(m+1, 0) &=& A(m, 1) \\ A(m+1, n+1)& = &A(m, A(m+1, n)) } $$
Ackermann's function, while Turing computable, grows faster than any primitive recursive function. The reason can be seen from the table: the index for the next value is also growing.
$$ A(0, n) = n + 1 \\ A(1, n) = 2 + (n + 3) - 3 \\ A(2, n) = 2 \times (n + 3) - 3 \\ A(3, n) = 2 n + 3 - 3 \\ A(4, n) = 2^{2^{\ldots^2}} - 3 \qquad (n + 3 \mbox{ terms}) \\ \ldots $$
remember that +++2^{2^{2^2}} = 2^{(2^{(2^2)})} = 65\,536+++, and not +++((2^2)^2)^2 = 2^{2 \times 2 \times 2} =256+++
Conventional mathematical notation breaks down at this point, and something more extensible is needed, invented specially to define big numbers.