Literature DB >> 26584365

Hybrid MPI-OpenMP Parallelism in the ONETEP Linear-Scaling Electronic Structure Code: Application to the Delamination of Cellulose Nanofibrils.

Karl A Wilkinson1, Nicholas D M Hine2, Chris-Kriton Skylaris1.   

Abstract

We present a hybrid MPI-OpenMP implementation of Linear-Scaling Density Functional Theory within the ONETEP code. We illustrate its performance on a range of high performance computing (HPC) platforms comprising shared-memory nodes with fast interconnect. Our work has focused on applying OpenMP parallelism to the routines which dominate the computational load, attempting where possible to parallelize different loops from those already parallelized within MPI. This includes 3D FFT box operations, sparse matrix algebra operations, calculation of integrals, and Ewald summation. While the underlying numerical methods are unchanged, these developments represent significant changes to the algorithms used within ONETEP to distribute the workload across CPU cores. The new hybrid code exhibits much-improved strong scaling relative to the MPI-only code and permits calculations with a much higher ratio of cores to atoms. These developments result in a significantly shorter time to solution than was possible using MPI alone and facilitate the application of the ONETEP code to systems larger than previously feasible. We illustrate this with benchmark calculations from an amyloid fibril trimer containing 41,907 atoms. We use the code to study the mechanism of delamination of cellulose nanofibrils when undergoing sonification, a process which is controlled by a large number of interactions that collectively determine the structural properties of the fibrils. Many energy evaluations were needed for these simulations, and as these systems comprise up to 21,276 atoms this would not have been feasible without the developments described here.

Entities:  

Year:  2014        PMID: 26584365     DOI: 10.1021/ct500686r

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  5 in total

1.  Introducing DDEC6 atomic population analysis: part 4. Efficient parallel computation of net atomic charges, atomic spin moments, bond orders, and more.

Authors:  Nidia Gabaldon Limas; Thomas A Manz
Journal:  RSC Adv       Date:  2018-01-11       Impact factor: 4.036

2.  New scaling relations to compute atom-in-material polarizabilities and dispersion coefficients: part 2. Linear-scaling computational algorithms and parallelization.

Authors:  Thomas A Manz; Taoyi Chen
Journal:  RSC Adv       Date:  2019-10-17       Impact factor: 4.036

3.  Biomolecular Force Field Parameterization via Atoms-in-Molecule Electron Density Partitioning.

Authors:  Daniel J Cole; Jonah Z Vilseck; Julian Tirado-Rives; Mike C Payne; William L Jorgensen
Journal:  J Chem Theory Comput       Date:  2016-04-21       Impact factor: 6.006

4.  Determination of band offsets, hybridization, and exciton binding in 2D semiconductor heterostructures.

Authors:  Neil R Wilson; Paul V Nguyen; Kyle Seyler; Pasqual Rivera; Alexander J Marsden; Zachary P L Laker; Gabriel C Constantinescu; Viktor Kandyba; Alexei Barinov; Nicholas D M Hine; Xiaodong Xu; David H Cobden
Journal:  Sci Adv       Date:  2017-02-08       Impact factor: 14.136

Review 5.  Machine learning for molecular and materials science.

Authors:  Keith T Butler; Daniel W Davies; Hugh Cartwright; Olexandr Isayev; Aron Walsh
Journal:  Nature       Date:  2018-07-25       Impact factor: 49.962

  5 in total

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