Identifying cost-effective common subexpressions to reduce operation count in tensor contraction evaluations

Albert Hartono; Qingda Lu; Xiaoyang Gao; Sriram Krishnamoorthy; Marcel Nooijen; Gerald Baumgartner; David E. Bernholdt; Venkatesh Choppella; Russell M. Pitzer; J. Ramanujam; Atanas Rountev; P. Sadayappan

doi:10.1007/11758501_39

Identifying cost-effective common subexpressions to reduce operation count in tensor contraction evaluations

Albert Hartono, Qingda Lu, Xiaoyang Gao, Sriram Krishnamoorthy, Marcel Nooijen, Gerald Baumgartner, David E. Bernholdt, Venkatesh Choppella, Russell M. Pitzer, J. Ramanujam, Atanas Rountev, P. Sadayappan

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

14 Scopus citations

Abstract

Complex tensor contraction expressions arise in accurate electronic structure models in quantum chemistry, such as the coupled cluster method. Transformations using algebraic properties of commutativity and associativity can be used to significantly decrease the number of arithmetic operations required for evaluation of these expressions. Operation minimization is an important optimization step for the Tensor Contraction Engine, a tool being developed for the automatic transformation of high-level tensor contraction expressions into efficient programs. The identification of common subexpressions among a set of tensor contraction expressions can result in a reduction of the total number of operations required to evaluate the tensor contractions. In this paper, we develop an effective algorithm for common subexpression identification and demonstrate its effectiveness on tensor contraction expressions for coupled cluster equations.

Original language	English
Title of host publication	Computational Science - ICCS 2006
Subtitle of host publication	6th International Conference, Proceedings
Publisher	Springer Verlag
Pages	267-275
Number of pages	9
ISBN (Print)	3540343792, 9783540343790
DOIs	https://doi.org/10.1007/11758501_39
State	Published - 2006
Event	ICCS 2006: 6th International Conference on Computational Science - Reading, United Kingdom Duration: May 28 2006 → May 31 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3991 LNCS - I
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	ICCS 2006: 6th International Conference on Computational Science
Country/Territory	United Kingdom
City	Reading
Period	05/28/06 → 05/31/06

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10.1007/11758501_39

Cite this

Hartono, A., Lu, Q., Gao, X., Krishnamoorthy, S., Nooijen, M., Baumgartner, G., Bernholdt, D. E., Choppella, V., Pitzer, R. M., Ramanujam, J., Rountev, A., & Sadayappan, P. (2006). Identifying cost-effective common subexpressions to reduce operation count in tensor contraction evaluations. In Computational Science - ICCS 2006: 6th International Conference, Proceedings (pp. 267-275). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3991 LNCS - I). Springer Verlag. https://doi.org/10.1007/11758501_39

Hartono, Albert ; Lu, Qingda ; Gao, Xiaoyang et al. / Identifying cost-effective common subexpressions to reduce operation count in tensor contraction evaluations. Computational Science - ICCS 2006: 6th International Conference, Proceedings. Springer Verlag, 2006. pp. 267-275 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Identifying cost-effective common subexpressions to reduce operation count in tensor contraction evaluations",

abstract = "Complex tensor contraction expressions arise in accurate electronic structure models in quantum chemistry, such as the coupled cluster method. Transformations using algebraic properties of commutativity and associativity can be used to significantly decrease the number of arithmetic operations required for evaluation of these expressions. Operation minimization is an important optimization step for the Tensor Contraction Engine, a tool being developed for the automatic transformation of high-level tensor contraction expressions into efficient programs. The identification of common subexpressions among a set of tensor contraction expressions can result in a reduction of the total number of operations required to evaluate the tensor contractions. In this paper, we develop an effective algorithm for common subexpression identification and demonstrate its effectiveness on tensor contraction expressions for coupled cluster equations.",

author = "Albert Hartono and Qingda Lu and Xiaoyang Gao and Sriram Krishnamoorthy and Marcel Nooijen and Gerald Baumgartner and Bernholdt, \{David E.\} and Venkatesh Choppella and Pitzer, \{Russell M.\} and J. Ramanujam and Atanas Rountev and P. Sadayappan",

year = "2006",

doi = "10.1007/11758501\_39",

language = "English",

isbn = "3540343792",

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

publisher = "Springer Verlag",

pages = "267--275",

booktitle = "Computational Science - ICCS 2006",

note = "ICCS 2006: 6th International Conference on Computational Science ; Conference date: 28-05-2006 Through 31-05-2006",

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Hartono, A, Lu, Q, Gao, X, Krishnamoorthy, S, Nooijen, M, Baumgartner, G, Bernholdt, DE, Choppella, V, Pitzer, RM, Ramanujam, J, Rountev, A & Sadayappan, P 2006, Identifying cost-effective common subexpressions to reduce operation count in tensor contraction evaluations. in Computational Science - ICCS 2006: 6th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3991 LNCS - I, Springer Verlag, pp. 267-275, ICCS 2006: 6th International Conference on Computational Science, Reading, United Kingdom, 05/28/06. https://doi.org/10.1007/11758501_39

Identifying cost-effective common subexpressions to reduce operation count in tensor contraction evaluations. / Hartono, Albert; Lu, Qingda; Gao, Xiaoyang et al.
Computational Science - ICCS 2006: 6th International Conference, Proceedings. Springer Verlag, 2006. p. 267-275 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3991 LNCS - I).

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

TY - GEN

T1 - Identifying cost-effective common subexpressions to reduce operation count in tensor contraction evaluations

AU - Hartono, Albert

AU - Lu, Qingda

AU - Gao, Xiaoyang

AU - Krishnamoorthy, Sriram

AU - Nooijen, Marcel

AU - Baumgartner, Gerald

AU - Bernholdt, David E.

AU - Choppella, Venkatesh

AU - Pitzer, Russell M.

AU - Ramanujam, J.

AU - Rountev, Atanas

AU - Sadayappan, P.

PY - 2006

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N2 - Complex tensor contraction expressions arise in accurate electronic structure models in quantum chemistry, such as the coupled cluster method. Transformations using algebraic properties of commutativity and associativity can be used to significantly decrease the number of arithmetic operations required for evaluation of these expressions. Operation minimization is an important optimization step for the Tensor Contraction Engine, a tool being developed for the automatic transformation of high-level tensor contraction expressions into efficient programs. The identification of common subexpressions among a set of tensor contraction expressions can result in a reduction of the total number of operations required to evaluate the tensor contractions. In this paper, we develop an effective algorithm for common subexpression identification and demonstrate its effectiveness on tensor contraction expressions for coupled cluster equations.

AB - Complex tensor contraction expressions arise in accurate electronic structure models in quantum chemistry, such as the coupled cluster method. Transformations using algebraic properties of commutativity and associativity can be used to significantly decrease the number of arithmetic operations required for evaluation of these expressions. Operation minimization is an important optimization step for the Tensor Contraction Engine, a tool being developed for the automatic transformation of high-level tensor contraction expressions into efficient programs. The identification of common subexpressions among a set of tensor contraction expressions can result in a reduction of the total number of operations required to evaluate the tensor contractions. In this paper, we develop an effective algorithm for common subexpression identification and demonstrate its effectiveness on tensor contraction expressions for coupled cluster equations.

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SN - 9783540343790

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

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BT - Computational Science - ICCS 2006

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T2 - ICCS 2006: 6th International Conference on Computational Science

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ER -

Hartono A, Lu Q, Gao X, Krishnamoorthy S, Nooijen M, Baumgartner G et al. Identifying cost-effective common subexpressions to reduce operation count in tensor contraction evaluations. In Computational Science - ICCS 2006: 6th International Conference, Proceedings. Springer Verlag. 2006. p. 267-275. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11758501_39

Identifying cost-effective common subexpressions to reduce operation count in tensor contraction evaluations

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