Parallelization Strategies for Density Matrix Renormalization Group Algorithms on Shared-Memory Systems

Details Parallelization Strategies for Density Matrix Renormalization Group Algorithms on Shared-Memory Systems Parallelization Strategies for Density Matrix Renormalization Group Algorithms on Shared-Memory Systems

2003-05-20

arxiv.org/abs/cond-mat/0305463v1

Journal of Computational Physics, 194 (2004) 795-808

Physics

Condensed Matter

Strongly Correlated Electrons

18 pages, 9 figures

Scientific paper

10.1016/j.jcp.2003.09.018

Shared-memory parallelization (SMP) strategies for density matrix renormalization group (DMRG) algorithms enable the treatment of complex systems in solid state physics. We present two different approaches by which parallelization of the standard DMRG algorithm can be accomplished in an efficient way. The methods are illustrated with DMRG calculations of the two-dimensional Hubbard model and the one-dimensional Holstein-Hubbard model on contemporary SMP architectures. The parallelized code shows good scalability up to at least eight processors and allows us to solve problems which exceed the capability of sequential DMRG calculations.

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