Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models
The conductor-like polarization model (C-PCM) with switching/Gaussian smooth discretization is a widely used implicit solvation model in chemical simulations. However, its application in quantum mechanical calculations of large-scale biomolecular systems can be limited by computational expense of bo...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | en_US |
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American Chemical Society (ACS)
2017
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| Online Access: | http://hdl.handle.net/1721.1/110571 https://orcid.org/0000-0001-9342-0191 |
| _version_ | 1811070179977723904 |
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| author | Liu, Fang Luehr, Nathan Martínez, Todd J. Kulik, Heather Janine |
| author2 | Massachusetts Institute of Technology. Department of Chemical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Chemical Engineering Liu, Fang Luehr, Nathan Martínez, Todd J. Kulik, Heather Janine |
| author_sort | Liu, Fang |
| collection | MIT |
| description | The conductor-like polarization model (C-PCM) with switching/Gaussian smooth discretization is a widely used implicit solvation model in chemical simulations. However, its application in quantum mechanical calculations of large-scale biomolecular systems can be limited by computational expense of both the gas phase electronic structure and the solvation interaction. We have previously used graphical processing units (GPUs) to accelerate the first of these steps. Here, we extend the use of GPUs to accelerate electronic structure calculations including C-PCM solvation. Implementation on the GPU leads to significant acceleration of the generation of the required integrals for C-PCM. We further propose two strategies to improve the solution of the required linear equations: a dynamic convergence threshold and a randomized block-Jacobi preconditioner. These strategies are not specific to GPUs and are expected to be beneficial for both CPU and GPU implementations. We benchmark the performance of the new implementation using over 20 small proteins in solvent environment. Using a single GPU, our method evaluates the C-PCM related integrals and their derivatives more than 10× faster than that with a conventional CPU-based implementation. Our improvements to the linear solver provide a further 3× acceleration. The overall calculations including C-PCM solvation require, typically, 20–40% more effort than that for their gas phase counterparts for a moderate basis set and molecule surface discretization level. The relative cost of the C-PCM solvation correction decreases as the basis sets and/or cavity radii increase. Therefore, description of solvation with this model should be routine. We also discuss applications to the study of the conformational landscape of an amyloid fibril. |
| first_indexed | 2024-09-23T08:30:18Z |
| format | Article |
| id | mit-1721.1/110571 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T08:30:18Z |
| publishDate | 2017 |
| publisher | American Chemical Society (ACS) |
| record_format | dspace |
| spelling | mit-1721.1/1105712022-09-30T09:25:47Z Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models Liu, Fang Luehr, Nathan Martínez, Todd J. Kulik, Heather Janine Massachusetts Institute of Technology. Department of Chemical Engineering Kulik, Heather Janine The conductor-like polarization model (C-PCM) with switching/Gaussian smooth discretization is a widely used implicit solvation model in chemical simulations. However, its application in quantum mechanical calculations of large-scale biomolecular systems can be limited by computational expense of both the gas phase electronic structure and the solvation interaction. We have previously used graphical processing units (GPUs) to accelerate the first of these steps. Here, we extend the use of GPUs to accelerate electronic structure calculations including C-PCM solvation. Implementation on the GPU leads to significant acceleration of the generation of the required integrals for C-PCM. We further propose two strategies to improve the solution of the required linear equations: a dynamic convergence threshold and a randomized block-Jacobi preconditioner. These strategies are not specific to GPUs and are expected to be beneficial for both CPU and GPU implementations. We benchmark the performance of the new implementation using over 20 small proteins in solvent environment. Using a single GPU, our method evaluates the C-PCM related integrals and their derivatives more than 10× faster than that with a conventional CPU-based implementation. Our improvements to the linear solver provide a further 3× acceleration. The overall calculations including C-PCM solvation require, typically, 20–40% more effort than that for their gas phase counterparts for a moderate basis set and molecule surface discretization level. The relative cost of the C-PCM solvation correction decreases as the basis sets and/or cavity radii increase. Therefore, description of solvation with this model should be routine. We also discuss applications to the study of the conformational landscape of an amyloid fibril. United States. Office of Naval Research (N00014-14-1-0590) 2017-07-10T14:07:48Z 2017-07-10T14:07:48Z 2015-06 2015-04 Article http://purl.org/eprint/type/JournalArticle 1549-9618 1549-9626 http://hdl.handle.net/1721.1/110571 Liu, Fang; Luehr, Nathan; Kulik, Heather J. and Martínez, Todd J. "Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models." Journal of Chemical Theory and Computation 11, 7 (July 2015): 3131–3144 © 2015 American Chemical Society https://orcid.org/0000-0001-9342-0191 en_US http://dx.doi.org/10.1021/acs.jctc.5b00370 Journal of Chemical Theory and Computation Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf American Chemical Society (ACS) arXiv |
| spellingShingle | Liu, Fang Luehr, Nathan Martínez, Todd J. Kulik, Heather Janine Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models |
| title | Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models |
| title_full | Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models |
| title_fullStr | Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models |
| title_full_unstemmed | Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models |
| title_short | Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models |
| title_sort | quantum chemistry for solvated molecules on graphical processing units using polarizable continuum models |
| url | http://hdl.handle.net/1721.1/110571 https://orcid.org/0000-0001-9342-0191 |
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