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pNeRF: Parallelized Conversion from Internal to Cartesian Coordinates

Mohammed AlQuraishi
doi: https://doi.org/10.1101/385450
Mohammed AlQuraishi
1Mohammed AlQuraishi, Department of Systems Biology, Harvard Medical School, 200 Longwood Ave., Boston, MA, USA, 02115
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ABSTRACT

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.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted August 06, 2018.
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pNeRF: Parallelized Conversion from Internal to Cartesian Coordinates
Mohammed AlQuraishi
bioRxiv 385450; doi: https://doi.org/10.1101/385450
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pNeRF: Parallelized Conversion from Internal to Cartesian Coordinates
Mohammed AlQuraishi
bioRxiv 385450; doi: https://doi.org/10.1101/385450

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