Parallelized Natural Extension Reference Frame : Parallelized Conversion from Internal to Cartesian Coordinates
© 2019 Wiley Periodicals, Inc.
| Veröffentlicht in: | Journal of computational chemistry. - 1984. - 40(2019), 7 vom: 15. März, Seite 885-892 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2019
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| Zugriff auf das übergeordnete Werk: | Journal of computational chemistry |
| Schlagworte: | Journal Article Research Support, N.I.H., Extramural internal coordinates machine learning molecular dynamics molecular mechanics protein structure Polymers |
| Zusammenfassung: | © 2019 Wiley Periodicals, Inc. The conversion of polymer parameterization from internal coordinates (bond lengths, angles, and torsions) to Cartesian coordinates is a fundamental task in molecular modeling, often performed using the natural extension reference frame (NeRF) algorithm. NeRF can be parallelized to process multiple polymers simultaneously, but is not parallelizable along the length of a single polymer. A mathematically equivalent algorithm, pNeRF, has been derived that is parallelizable along a polymer's length. Empirical analysis demonstrates an order-of-magnitude speed up using modern GPUs and CPUs. In machine learning-based workflows, in which partial derivatives are backpropagated through NeRF equations and neural network primitives, switching to pNeRF can reduce the fractional computational cost of coordinate conversion from over two-thirds to around 10%. An optimized TensorFlow-based implementation of pNeRF is available on GitHub at https://github.com/aqlaboratory/pnerf © 2018 Wiley Periodicals, Inc |
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| Beschreibung: | Date Completed 16.06.2020 Date Revised 16.06.2020 published: Print-Electronic Citation Status MEDLINE |
| ISSN: | 1096-987X |
| DOI: | 10.1002/jcc.25772 |