A one billion determinant full CI benchmark on the Cray T3D

Evangelisti, Stefano; Bendazzoli, Gian Luigi; Ansaloni, Roberto; Durì, Francesca; Rossi, Elda

doi:10.1016/0009-2614(96)00177-7

Cited by 31 publications

(21 citation statements)

References 28 publications

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“…Recent high-level calculations suggest even higher binding energies: for instance, Stärck and Meyer [11] (SM), using MRCI (multireference configuration interaction) and a core polarization potential (CPP) found D e =893 cm −1 as well as r e =2.448 5Å , while MR-AQCC (multireference averaged quadratic coupled cluster [12]) calculations by Füsti-Molnár and Szalay [13] (FS) established D e =864 cm −1 as a lower bound. Røeggen [15].…”

Section: Introductionmentioning

confidence: 99%

The ground-state spectroscopic constants of Be2 revisited

Martin¹

1999

Chemical Physics Letters

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Section: Introductionmentioning

confidence: 99%

The ground-state spectroscopic constants of Be2 revisited

Martin¹

1999

Chemical Physics Letters

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“…The concept of approximating or averaging diagonal matrix elements to enhance algorithmic performance or preserve spin properties has existed in the literature for some time. 14,44 Recently, Evangelisti et al 16,38 have suggested several schemes that enable efficient on-the-fly evaluation of average diagonal Hamiltonian elements, thus eliminating the need to store the entire diagonal vector on disk or in core memory. The first approach 38 is simply to use the sum of orbital energies ( i ) of the occupied orbitals for each determinant, a relatively crude estimate, which, unlike eq.…”

Section: Approximate Diagonal Elementsmentioning

confidence: 99%

“…(21), does not attempt to correct for overcounting of two-electron interactions. A more accurate approach 16 is to evaluate a diagonal element as…”

Section: Approximate Diagonal Elementsmentioning

confidence: 99%

Systematic Study of Selected Diagonalization Methods for Configuration Interaction Matrices

et al. 2001

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Several modifications to the Davidson algorithm are systematically explored to establish their performance for an assortment of configuration interaction (CI) computations. The combination of a generalized Davidson method, a periodic two-vector subspace collapse, and a blocked Davidson approach for multiple roots is determined to retain the convergence characteristics of the full subspace method. This approach permits the efficient computation of wave functions for large-scale CI matrices by eliminating the need to ever store more than three expansion vectors (b i ) and associated matrix-vector products (σ i ), thereby dramatically reducing the I/O requirements relative to the full subspace scheme. The minimal-storage, single-vector method of Olsen is found to be a reasonable alternative for obtaining energies of well-behaved systems to within µE h accuracy, although it typically requires around 50% more iterations and at times is too inefficient to yield high accuracy (ca. 10−10 E h ) for very large CI problems. Several approximations to the diagonal elements of the CI Hamiltonian matrix are found to allow simple on-the-fly computation of the preconditioning matrix, to maintain the spin symmetry of the determinant-based wave function, and to preserve the convergence characteristics of the diagonalization procedure.

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“…In sequential minimum operation count (MOC) algorithms [2][3][4][5][6][7] only the non-zero Hamiltonian matrix elements are computed, and the vector is updated by indexed multiply and add operations. However, on cache-based computer systems the indexed operations generally perform poorly.…”

Section: Dgemm Based Fci Algorithmmentioning

confidence: 99%

“…Parallel FCI algorithms on massive parallel architectures (MPP) [3,4,5,6] as well as clusters of workstation [7] have been widely pursued. However, efficient utilization of both these architectures remains a challenging task because of the huge sparse matrix vector multiplication performed.…”

Section: Introductionmentioning

confidence: 99%

Calibrating quantum chemistry: A multi-teraflop, parallel-vector, full-configuration interaction program for the Cray-X1

Gan

Harrison

ACM/IEEE SC 2005 Conference (SC'05)

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We describe an efficient parallel and vector algorithm for solving huge eigen-vector problems in quantum chemistry. An automatically adaptive, single-vector, iterative diagonalization method was also developed to reduce the memory requirement and avoid an I/O bottleneck. Our initial full-configuration interaction calculation solved for an eigenvector with 65 billion coefficients and was performed on 432 MSPs of the Oak Ridge National Laboratory Cray-X1. One matrixvector multiplication took about 4 minutes, with 25 iterations being required for a tightly converged result. The aggregate performance was 3.4TFLOP/s (62% of peak speed).

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A one billion determinant full CI benchmark on the Cray T3D

Cited by 31 publications

References 28 publications

The ground-state spectroscopic constants of Be2 revisited

The ground-state spectroscopic constants of Be2 revisited

Systematic Study of Selected Diagonalization Methods for Configuration Interaction Matrices

Calibrating quantum chemistry: A multi-teraflop, parallel-vector, full-configuration interaction program for the Cray-X1

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