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Developed in-house and maintained

The following is a list of software and numerical libraries developed and maintained in-house by the SLQM team.

  • Numerical linear algebra libraries (JuNLib)

    • ChASE: Chebyshev Accelerated Subspace iteration Eigensolver.
      It is a modern interpretation of the original algorithm proposed by Rutishauser in 1969. The library contains algorithmic improvements, such as an optimization scheme for the polynomial degree and a precise estimate for the filter bounds, and targets modern heterogeneous computing platforms.
      Contact: E. Di Napoli
    • PAID: Parallel Adaptive Integration in multiple Dimensions.
      Library for adaptive integration based on Clenshaw-Curtis method parallelized for shared memory platforms.
      Contact: J. Winkelmann
    • SMG2S (Scalable Matrix Generator with Given Spectrum)

      SMG2S is a software which provides generator for the non-Symmetric and non-Hermitian sparse matrices with eigenvalues given by users. It is proposed to benchmark and analyse the impacts of the spectral distribution of systems on the behaviours of parallel iterative eigen-solvers and linear-solvers. SMG2S is implemented in parallel based on MPI and C++11 with good parallel efficiency. (Code)

      Contact: X. Wu

  • Simulation Software

    • KKRnano as part of juKKR
      A simulation code based on the Korringa-Kohn-Rostoker formalism tailored to nanoelectronic simulations which scales linearly with the number of atoms. The tfQMRgpu library allows to solve the Dyson equation on NVIDIA GPUs.
      Contact: P. Baumeister
    • juRS: The Jülich Real-Space code.
      Density Functional Theory code based on real-space discretization grid which uses hybrid parallelism and Blöchl’s PAW formalism to get full potential accuracy.
      Contact: P. Baumeister
    • 1D-NEGF.
      Non-Equilibrium Green's Functions for transport phenomena.
      Contact: S. Achilles,
    • neXGf
      Contact: P. Baumeister,S. Achilles


The following is a list of the simulation software supported by the SLQM team.