Large-scale ab initio configuration interaction calculations for light nuclei

Maris, Pieter; Aktulga, Hasan Metin; Caprio, M. A.; Çatalyürek, Ümit V.; Ng, Esmond G.; Oryspayev, Dossay; Potter, Hugh; Saule, Érik; Sosonkina, Masha; Vary, James P.; Yang, Chao; Zhou, Zheng

doi:10.1088/1742-6596/403/1/012019

Cited by 32 publications

(32 citation statements)

References 19 publications

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“…Ω dependence) and λ dependence. We also see this in 12 C, where the lowest 2 + and 4 + states form a rotational band with the ground state [33], but other low-lying states in 12 C are much more sensitive to the 3NFs and have a different convergence pattern [37].…”

Section: Fig 19 (Color Online) Extrapolated Ground-state Energy Ofmentioning

confidence: 83%

“…The calculations were performed on the Intel Xeon cluster Sierra at LLNL, using up to about 15 TB of memory across 7,200 cores on the Cray XE6 Hopper at NERSC, using up to about 100 TB of memory across 76,320 cores; and on the Cray XK6 Jaguar at ORNL, using over 500 TB of memory across 261,120 cores. MFDn has been demonstrated to scale well on these platforms for these types of runs [33].…”

Section: -8mentioning

confidence: 99%

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Structure ofp-shell nuclei using three-nucleon interactions evolved with the similarity renormalization group

et al. 2013

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The Similarity Renormalization Group (SRG) is used to soften interactions for ab initio nuclear structure calculations by decoupling low-and high-energy Hamiltonian matrix elements. The substantial contribution of both initial and SRG-induced three-nucleon forces requires their consistent evolution in a three-particle basis space before applying them to larger nuclei. While in principle the evolved Hamiltonians are unitarily equivalent, in practice the need for basis truncation introduces deviations, which must be monitored. Here we present benchmark no-core full configuration calculations with SRG-evolved interactions in p-shell nuclei over a wide range of softening. These calculations are used to assess convergence properties, extrapolation techniques, and the dependence of energies, including four-body contributions, on the SRG resolution scale.

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Section: Fig 19 (Color Online) Extrapolated Ground-state Energy Ofmentioning

confidence: 83%

Section: -8mentioning

confidence: 99%

Structure ofp-shell nuclei using three-nucleon interactions evolved with the similarity renormalization group

et al. 2013

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“…The Many-body Fermion Dynamics for nuclei (MFDn) code is a nuclear physics code in which the lowest few eigenvalues and eigenvectors of a very large real sparse symmetric matrix are found though iterative means [12]. Sparse matrix vector and and sparse matrix transpose vector products are key kernels in the iterative eigensolver.…”

Section: Mfdnmentioning

confidence: 99%

Applying the Roofline Performance Model to the Intel Xeon Phi Knights Landing Processor

Doerfler

Deslippe

Williams

et al. 2016

Lecture Notes in Computer Science

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“…capabilities during the UNEDF project [22]. The current scaling performance of mfdn is demonstrated in Fig.…”

Section: Ncsm and Mfdnmentioning

confidence: 99%

Computational nuclear quantum many-body problem: The UNEDF project

Bogner

Bulgac

Carlson

et al. 2013

Computer Physics Communications

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The UNEDF project was a large-scale collaborative effort that applied high-performance computing to the nuclear quantum many-body problem. UNEDF demonstrated that close associations among nuclear physicists, mathematicians, and computer scientists can lead to novel physics outcomes built on algorithmic innovations and computational developments. This review showcases a wide range of UNEDF science results to illustrate this interplay.

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Large-scale ab initio configuration interaction calculations for light nuclei

Cited by 32 publications

References 19 publications

Structure ofp-shell nuclei using three-nucleon interactions evolved with the similarity renormalization group

Structure ofp-shell nuclei using three-nucleon interactions evolved with the similarity renormalization group

Applying the Roofline Performance Model to the Intel Xeon Phi Knights Landing Processor

Computational nuclear quantum many-body problem: The UNEDF project

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