Parallelization strategies for density matrix renormalization group algorithms on shared-memory systems

Shared-memory (SMP) parallelization 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 wa...

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Vydané v:Journal of computational physics Ročník 194; číslo 2; s. 795 - 808
Hlavní autori: Hager, G., Jeckelmann, E., Fehske, H., Wellein, G.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Amsterdam Elsevier Inc 01.03.2004
Elsevier
Predmet:
Computational techniques
Exact sciences and technology
Mathematical methods in physics
Physics
Algorithms
Complex system
Density matrix
Two-dimensional calculations
Two dimensional model
Calculation
Renormalization group
Calculation methods
ISSN:0021-9991, 1090-2716
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Popis
Shrnutí:Shared-memory (SMP) parallelization 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.
Bibliografia:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0021-9991
1090-2716
DOI:10.1016/j.jcp.2003.09.018