The complexity of Covariance matrix computation is O(p2n). Its eigenvalue decomposition is O(p3). So, the complexity of PCA is O(p2n+p3).
O(min(p3,n3)) would imply that you could analyze a two-dimensional dataset of any size in a fixed time.
For more details on the abovementioned topics, study Principal Component Analysis. One can also study Machine Learning Algorithms for a better grasp.
Hope this answer helps you!