  In one of the most important methods in Density Functional Theory - the
Full-Potential Linearized Augmented Plane Wave (FLAPW) method - dense
generalized eigenproblems are organized in long sequences. Moreover each
eigenproblem is strongly correlated to the next one in the sequence. We propose
a novel approach which exploits such correlation through the use of an
eigensolver based on subspace iteration and accelerated with Chebyshev
polynomials. The resulting solver, parallelized using the Elemental library
framework, achieves excellent scalability and is competitive with current dense
parallel eigensolvers.
