The HPPRINCOMP procedure implements several algorithms to calculate principal components: eigenvalue decomposition, NIPALS, and ITERGS of Andrecut (2009). Eigenvalue decomposition is more efficient when you want to calculate all principal components, whereas the NIPALS method is faster if you want to extract only the first few principal components. For high-dimensional data sets, the NIPALS method is more efficient, whereas it gets expensive for eigenvalue decomposition to calculate all the components simultaneously.