Data reduction schemes in davidson subspace diagonalization for MR-CI

Wilfried N. Gansterer; Wolfgang Kreuzer; Hans Lischka

doi:10.1007/11666806_64

Data reduction schemes in davidson subspace diagonalization for MR-CI

Wilfried N. Gansterer, Wolfgang Kreuzer, Hans Lischka

Chemistry and Biochemistry

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

In this paper, we investigate several data reduction schemes to improve the computational efficiency in the multi reference configuration interaction (MR-CI) method, one of the main quantum chemical approaches for solving the electronic Schrödinger equation, The basic idea is to take advantage of the often relatively low accuracy requirements on the solution of the resulting large eigenvalue problem, whose dimension may reach several hundred millions or even more. We will discuss some approaches to reduce the amount of data to be accessed and to be transferred within the Davidson subspace diagonalization method. We also show experimental results achieved with the COLUMBUS code.

Original language	English
Title of host publication	Large-Scale Scientific Computing - 5th International Conference, LSSC 2005, Revised Papers
Pages	564-571
Number of pages	8
DOIs	https://doi.org/10.1007/11666806_64
State	Published - 2006
Event	5th International Conference on Large-Scale Scientific Computing, LSSC 2005 - Sozopol, Bulgaria Duration: Jun 6 2005 → Jun 10 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3743 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	5th International Conference on Large-Scale Scientific Computing, LSSC 2005
Country/Territory	Bulgaria
City	Sozopol
Period	06/6/05 → 06/10/05

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10.1007/11666806_64

Cite this

Gansterer, W. N., Kreuzer, W., & Lischka, H. (2006). Data reduction schemes in davidson subspace diagonalization for MR-CI. In Large-Scale Scientific Computing - 5th International Conference, LSSC 2005, Revised Papers (pp. 564-571). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3743 LNCS). https://doi.org/10.1007/11666806_64

Gansterer, Wilfried N. ; Kreuzer, Wolfgang ; Lischka, Hans. / Data reduction schemes in davidson subspace diagonalization for MR-CI. Large-Scale Scientific Computing - 5th International Conference, LSSC 2005, Revised Papers. 2006. pp. 564-571 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Data reduction schemes in davidson subspace diagonalization for MR-CI",

abstract = "In this paper, we investigate several data reduction schemes to improve the computational efficiency in the multi reference configuration interaction (MR-CI) method, one of the main quantum chemical approaches for solving the electronic Schr{\"o}dinger equation, The basic idea is to take advantage of the often relatively low accuracy requirements on the solution of the resulting large eigenvalue problem, whose dimension may reach several hundred millions or even more. We will discuss some approaches to reduce the amount of data to be accessed and to be transferred within the Davidson subspace diagonalization method. We also show experimental results achieved with the COLUMBUS code.",

author = "Gansterer, {Wilfried N.} and Wolfgang Kreuzer and Hans Lischka",

year = "2006",

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language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "564--571",

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note = "5th International Conference on Large-Scale Scientific Computing, LSSC 2005 ; Conference date: 06-06-2005 Through 10-06-2005",

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Gansterer, WN, Kreuzer, W & Lischka, H 2006, Data reduction schemes in davidson subspace diagonalization for MR-CI. in Large-Scale Scientific Computing - 5th International Conference, LSSC 2005, Revised Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3743 LNCS, pp. 564-571, 5th International Conference on Large-Scale Scientific Computing, LSSC 2005, Sozopol, Bulgaria, 06/6/05. https://doi.org/10.1007/11666806_64

Data reduction schemes in davidson subspace diagonalization for MR-CI. / Gansterer, Wilfried N.; Kreuzer, Wolfgang; Lischka, Hans.
Large-Scale Scientific Computing - 5th International Conference, LSSC 2005, Revised Papers. 2006. p. 564-571 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3743 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - In this paper, we investigate several data reduction schemes to improve the computational efficiency in the multi reference configuration interaction (MR-CI) method, one of the main quantum chemical approaches for solving the electronic Schrödinger equation, The basic idea is to take advantage of the often relatively low accuracy requirements on the solution of the resulting large eigenvalue problem, whose dimension may reach several hundred millions or even more. We will discuss some approaches to reduce the amount of data to be accessed and to be transferred within the Davidson subspace diagonalization method. We also show experimental results achieved with the COLUMBUS code.

AB - In this paper, we investigate several data reduction schemes to improve the computational efficiency in the multi reference configuration interaction (MR-CI) method, one of the main quantum chemical approaches for solving the electronic Schrödinger equation, The basic idea is to take advantage of the often relatively low accuracy requirements on the solution of the resulting large eigenvalue problem, whose dimension may reach several hundred millions or even more. We will discuss some approaches to reduce the amount of data to be accessed and to be transferred within the Davidson subspace diagonalization method. We also show experimental results achieved with the COLUMBUS code.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Gansterer WN, Kreuzer W, Lischka H. Data reduction schemes in davidson subspace diagonalization for MR-CI. In Large-Scale Scientific Computing - 5th International Conference, LSSC 2005, Revised Papers. 2006. p. 564-571. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11666806_64

Data reduction schemes in davidson subspace diagonalization for MR-CI

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