  We present an accurate, efficient and massively parallel finite-element code,
DFT-FE, for large-scale ab-initio calculations (reaching $\sim 100,000$
electrons) using Kohn-Sham density functional theory (DFT). DFT-FE is based on
a local real-space variational formulation of the Kohn-Sham DFT energy
functional that is discretized using a higher-order adaptive spectral
finite-element (FE) basis, and treats pseudopotential and all-electron
calculations in the same framework, while accommodating non-periodic,
semi-periodic and periodic boundary conditions. We discuss the main aspects of
the code, which include, the various strategies of adaptive FE basis
generation, and the different approaches employed in the numerical
implementation of the solution of the discrete Kohn-Sham problem that are
focused on significantly reducing the floating point operations, communication
costs and latency. We demonstrate the accuracy of DFT-FE by comparing the
energies, ionic forces and periodic cell stresses on a wide range of problems
with popularly used DFT codes. Further, we demonstrate that DFT-FE
significantly outperforms widely used plane-wave codes---both in CPU-times and
wall-times, and on both non-periodic and periodic systems---at systems sizes
beyond a few thousand electrons, with over $5-10$ fold speedups in systems with
more than 10,000 electrons. The benchmark studies also highlight the excellent
parallel scalability of DFT-FE, with strong scaling demonstrated on up to
192,000 MPI tasks.
