A Robust and Efficient Implementation of LOBPCG

Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) is widely used to compute eigenvalues of large sparse symmetric matrices. The algorithm can suffer from numerical instability if it is not implemented with care. This is especially problematic when the number of eigenpairs to be computed is relatively large. We present a number of techniques to improve the robustness and efficiency of this algorithm. We show that our approach consistently and significantly outperforms previous competing approaches in both stability and speed. We also present a robust convergence criterion which is backward stable.