Parallel Eigensolvers Based on Minimization Strategies This presentation will show recent developments in unconstrained minimization strategies for the solution of eigenvalue problems in electronic structure calculations. These schemes employ a preconditioned conjugate gradient approach that avoids an explicit reorthogonalization of the trial eigenvectors, in contrast to typical iterative eigensolvers, therefore reducing communications and becoming an attractive approach for the solution of very large problems on massively parallel computers. The presentation will also discuss the need to rearrange calculations (sometimes counteractively) to achieve performance, in particular on GPUs.