Step 1: Observe structure of the matrix.
The first two rows of \(A\) are identical. Hence, the matrix is rank-deficient,
and one eigenvalue must be \(0.\)
Step 2: Simplify using linear dependence.
Let’s find the characteristic polynomial:
\[
\det(A - \lambda I) =
\begin{vmatrix}
2-\lambda & -1 & 3 \\
2 & -1-\lambda & 3 \\
3 & 2 & -1-\lambda
\end{vmatrix}.
\]
Step 3: Expand determinant.
Using expansion along the first row:
\[
(2-\lambda)
\begin{vmatrix}
-1-\lambda & 3 \\ 2 & -1-\lambda
\end{vmatrix}
+ 1
\begin{vmatrix}
2 & 3 \\ 3 & -1-\lambda
\end{vmatrix}
+ 3
\begin{vmatrix}
2 & -1-\lambda \\ 3 & 2
\end{vmatrix}.
\]
Simplifying gives:
\[
(2-\lambda)((-1-\lambda)^2 - 6) + (2(-1-\lambda) - 9) + 3(4 + 3(1+\lambda)).
\]
\[
(2-\lambda)(\lambda^2 + 2\lambda - 5) + (-2 - 2\lambda - 9) + (12 + 9 + 9\lambda).
\]
\[
(2-\lambda)(\lambda^2 + 2\lambda - 5) + (-11 - 2\lambda + 21 + 9\lambda).
\]
\[
(2-\lambda)(\lambda^2 + 2\lambda - 5) + (10 + 7\lambda).
\]
Expanding:
\[
2\lambda^2 + 4\lambda - 10 - \lambda^3 - 2\lambda^2 + 5\lambda + 10 + 7\lambda.
\]
Simplify:
\[
-\lambda^3 + 16\lambda.
\]
Step 4: Solve for eigenvalues.
\[
\lambda(-\lambda^2 + 16) = 0 \Rightarrow \lambda = 0,\; \pm 4.
\]
Step 5: Conclusion.
Largest eigenvalue \(= \boxed{4}.\)