A toolchain for the automatic generation of computer codes for correlated wavefunction calculations

In this work, the automated generator environment for ORCA (ORCA‐AGE) is described. It is a powerful toolchain for the automatic implementation of wavefunction‐based quantum chemical methods. ORCA‐AGE consists of three main modules: (1) generation of “raw” equations from a second quantized Ansatz fo...

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Published in:Journal of Computational Chemistry
Main Authors: Krupička, M., Sivalingam, K., Huntington, L., Auer, A., Neese, F.
Format: Article in Journal/Newspaper
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/21.11116/0000-0007-6F45-0
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spelling ftpubman:oai:pure.mpg.de:item_3264890 2023-08-27T04:11:25+02:00 A toolchain for the automatic generation of computer codes for correlated wavefunction calculations Krupička, M. Sivalingam, K. Huntington, L. Auer, A. Neese, F. 2017-08-05 http://hdl.handle.net/21.11116/0000-0007-6F45-0 eng eng info:eu-repo/semantics/altIdentifier/doi/10.1002/jcc.24833 http://hdl.handle.net/21.11116/0000-0007-6F45-0 Journal of Computational Chemistry info:eu-repo/semantics/article 2017 ftpubman https://doi.org/10.1002/jcc.24833 2023-08-02T00:24:25Z In this work, the automated generator environment for ORCA (ORCA‐AGE) is described. It is a powerful toolchain for the automatic implementation of wavefunction‐based quantum chemical methods. ORCA‐AGE consists of three main modules: (1) generation of “raw” equations from a second quantized Ansatz for the wavefunction, (2) factorization and optimization of equations, and (3) generation of actual computer code. We generate code for the ORCA package, making use of the powerful functionality for wavefunction‐based correlation calculations that is already present in the code. The equation generation makes use of the most elementary commutation relations and hence is extremely general. Consequently, code can be generated for single reference as well as multireference approaches and spin‐independent as well as spin‐dependent operators. The performance of the generated code is demonstrated through comparison with efficient hand‐optimized code for some well‐understood standard configuration interaction and coupled cluster methods. In general, the speed of the generated code is no more than 30% slower than the hand‐optimized code, thus allowing for routine application of canonical ab initio methods to molecules with about 500–1000 basis functions. Using the toolchain, complicated methods, especially those surpassing human ability for handling complexity, can be efficiently and reliably implemented in very short times. This enables the developer to shift the attention from debugging code to the physical content of the chosen wavefunction Ansatz. Automatic code generation also has the desirable property that any improvement in the toolchain immediately applies to all generated code. Article in Journal/Newspaper Orca Max Planck Society: MPG.PuRe Journal of Computational Chemistry 38 21 1853 1868
institution Open Polar
collection Max Planck Society: MPG.PuRe
op_collection_id ftpubman
language English
description In this work, the automated generator environment for ORCA (ORCA‐AGE) is described. It is a powerful toolchain for the automatic implementation of wavefunction‐based quantum chemical methods. ORCA‐AGE consists of three main modules: (1) generation of “raw” equations from a second quantized Ansatz for the wavefunction, (2) factorization and optimization of equations, and (3) generation of actual computer code. We generate code for the ORCA package, making use of the powerful functionality for wavefunction‐based correlation calculations that is already present in the code. The equation generation makes use of the most elementary commutation relations and hence is extremely general. Consequently, code can be generated for single reference as well as multireference approaches and spin‐independent as well as spin‐dependent operators. The performance of the generated code is demonstrated through comparison with efficient hand‐optimized code for some well‐understood standard configuration interaction and coupled cluster methods. In general, the speed of the generated code is no more than 30% slower than the hand‐optimized code, thus allowing for routine application of canonical ab initio methods to molecules with about 500–1000 basis functions. Using the toolchain, complicated methods, especially those surpassing human ability for handling complexity, can be efficiently and reliably implemented in very short times. This enables the developer to shift the attention from debugging code to the physical content of the chosen wavefunction Ansatz. Automatic code generation also has the desirable property that any improvement in the toolchain immediately applies to all generated code.
format Article in Journal/Newspaper
author Krupička, M.
Sivalingam, K.
Huntington, L.
Auer, A.
Neese, F.
spellingShingle Krupička, M.
Sivalingam, K.
Huntington, L.
Auer, A.
Neese, F.
A toolchain for the automatic generation of computer codes for correlated wavefunction calculations
author_facet Krupička, M.
Sivalingam, K.
Huntington, L.
Auer, A.
Neese, F.
author_sort Krupička, M.
title A toolchain for the automatic generation of computer codes for correlated wavefunction calculations
title_short A toolchain for the automatic generation of computer codes for correlated wavefunction calculations
title_full A toolchain for the automatic generation of computer codes for correlated wavefunction calculations
title_fullStr A toolchain for the automatic generation of computer codes for correlated wavefunction calculations
title_full_unstemmed A toolchain for the automatic generation of computer codes for correlated wavefunction calculations
title_sort toolchain for the automatic generation of computer codes for correlated wavefunction calculations
publishDate 2017
url http://hdl.handle.net/21.11116/0000-0007-6F45-0
genre Orca
genre_facet Orca
op_source Journal of Computational Chemistry
op_relation info:eu-repo/semantics/altIdentifier/doi/10.1002/jcc.24833
http://hdl.handle.net/21.11116/0000-0007-6F45-0
op_doi https://doi.org/10.1002/jcc.24833
container_title Journal of Computational Chemistry
container_volume 38
container_issue 21
container_start_page 1853
op_container_end_page 1868
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