A hybrid method for the parallel computation of Green's functions

Dan Erik Petersen, Song Li, Kurt Stokbro, Hans Henrik Brandenborg Sørensen, Per Christian Hansen, Stig Skelboe, Eric Darve

    Research output: Contribution to journalJournal articleResearchpeer-review


    Quantum transport models for nanodevices using the non-equilibrium Green's function method require the repeated calculation of the block tridiagonal part of the Green's and lesser Green's function matrices. This problem is related to the calculation of the inverse of a sparse matrix. Because of the large number of times this calculation needs to be performed, this is computationally very expensive even on supercomputers. The classical approach is based on recurrence formulas which cannot be efficiently parallelized. This practically prevents the solution of large problems with hundreds of thousands of atoms. We propose new recurrences for a general class of sparse matrices to calculate Green's and lesser Green's function matrices which extend formulas derived by Takahashi and others. We show that these recurrences may lead to a dramatically reduced computational cost because they only require computing a small number of entries of the inverse matrix. Then. we propose a parallelization strategy for block tridiagonal matrices which involves a combination of Schur complement calculations and cyclic reduction. It achieves good scalability even on problems of modest size.
    Original languageEnglish
    JournalJournal of Computational Physics
    Issue number14
    Pages (from-to)5020-5039
    Publication statusPublished - 2009


    • Green's function
    • Parallel computing
    • Nested dissection
    • Quantum transport
    • Density functional theory
    • Sparse matrix
    • Inverse matrix
    • Cyclic reduction

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