  We present CheSS, the "Chebyshev Sparse Solvers" library, which has been
designed to solve typical problems arising in large-scale electronic structure
calculations using localized basis sets. The library is based on a flexible and
efficient expansion in terms of Chebyshev polynomials and presently features
the calculation of the density matrix, the calculation of matrix powers for
arbitrary powers, and the extraction of eigenvalues in a selected interval.
CheSS is able to exploit the sparsity of the matrices and scales linearly with
respect to the number of nonzero entries, making it well-suited for large-scale
calculations. The approach is particularly adapted for setups leading to small
spectral widths of the involved matrices and outperforms alternative methods in
this regime. By coupling CheSS to the DFT code BigDFT, we show that such a
favorable setup is indeed possible in practice. In addition, the approach based
on Chebyshev polynomials can be massively parallelized, and CheSS exhibits
excellent scaling up to thousands of cores even for relatively small matrix
sizes.
