  We suggest and implement a parallelization scheme based on an efficient
multiband eigenvalue solver, called the locally optimal block preconditioned
conjugate gradient LOBPCG method, and using an optimized three-dimensional (3D)
fast Fourier transform (FFT) in the ab initio}plane-wave code ABINIT. In
addition to the standard data partitioning over processors corresponding to
different k-points, we introduce data partitioning with respect to blocks of
bands as well as spatial partitioning in the Fourier space of coefficients over
the plane waves basis set used in ABINIT. This k-points-multiband-FFT
parallelization avoids any collective communications on the whole set of
processors relying instead on one-dimensional communications only. For a single
k-point, super-linear scaling is achieved for up to 100 processors due to an
extensive use of hardware optimized BLAS, LAPACK, and SCALAPACK routines,
mainly in the LOBPCG routine. We observe good performance up to 200 processors.
With 10 k-points our three-way data partitioning results in linear scaling up
to 1000 processors for a practical system used for testing.
