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DCA++: A software framework to solve correlated electron problems with modern quantum cluster methods

Authors: Urs R. Hähner; Gonzalo Alvarez; Thomas A. Maier; Raffaele Solcà; Peter W. J. Staar; Michael S. Summers; Thomas C. Schulthess;

DCA++: A software framework to solve correlated electron problems with modern quantum cluster methods

Abstract

We present the first open release of the DCA++ project, a high-performance research software framework to solve quantum many-body problems with cutting edge quantum cluster algorithms. DCA++ implements the dynamical cluster approximation (DCA) and its DCA$^+$ extension with a continuous self-energy. The algorithms capture nonlocal correlations in strongly correlated electron systems, thereby giving insight into high-$T_c$ superconductivity. The code's scalability allows efficient usage of systems at all scales, from workstations to leadership computers. With regard to the increasing heterogeneity of modern computing machines, DCA++ provides portable performance on conventional and emerging new architectures, such as hybrid CPU-GPU, sustaining multiple petaflops on ORNL's Titan and CSCS' Piz Daint supercomputers. Moreover, we show how sustainable and scalable development of the code base has been achieved by adopting standard techniques of the software industry. These include employing a distributed version control system, applying test-driven development and following continuous integration.

32 pages, 17 figures, 1 table, 3 code listings; submitted to Comput. Phys. Commun

Country
Switzerland
Keywords

Strongly Correlated Electrons (cond-mat.str-el), FOS: Physical sciences, Strongly correlated electron systems, Dynamical cluster approximation, Computational Physics (physics.comp-ph), Condensed Matter - Strongly Correlated Electrons, Quantum cluster algorithms, Continuous-time quantum Monte Carlo, Extreme-scale computing, Sustainable software development, Physics - Computational Physics, Strongly correlated electron systems; Quantum cluster algorithms; Dynamical cluster approximation; Continuous-time quantum Monte Carlo; Extreme-scale computing; Sustainable software development

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    popularity
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    Top 10%
    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
28
Top 10%
Top 10%
Top 10%
Green
hybrid