Literature DB >> 31260119

More bang for your buck: Improved use of GPU nodes for GROMACS 2018.

Carsten Kutzner1, Szilárd Páll2, Martin Fechner1, Ansgar Esztermann1, Bert L de Groot1, Helmut Grubmüller1.   

Abstract

We identify hardware that is optimal to produce molecular dynamics (MD) trajectories on Linux compute clusters with the GROMACS 2018 simulation package. Therefore, we benchmark the GROMACS performance on a diverse set of compute nodes and relate it to the costs of the nodes, which may include their lifetime costs for energy and cooling. In agreement with our earlier investigation using GROMACS 4.6 on hardware of 2014, the performance to price ratio of consumer GPU nodes is considerably higher than that of CPU nodes. However, with GROMACS 2018, the optimal CPU to GPU processing power balance has shifted even more toward the GPU. Hence, nodes optimized for GROMACS 2018 and later versions enable a significantly higher performance to price ratio than nodes optimized for older GROMACS versions. Moreover, the shift toward GPU processing allows to cheaply upgrade old nodes with recent GPUs, yielding essentially the same performance as comparable brand-new hardware.
© 2019 Wiley Periodicals, Inc. © 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  CUDA; GPU; GROMACS; benchmark; computer simulations; energy efficiency; high throughput MD; molecular dynamics; parallel computing; performance to price

Year:  2019        PMID: 31260119     DOI: 10.1002/jcc.26011

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  55 in total

1.  Dynamic Docking Using Multicanonical Molecular Dynamics: Simulating Complex Formation at the Atomistic Level.

Authors:  Gert-Jan Bekker; Narutoshi Kamiya
Journal:  Methods Mol Biol       Date:  2021

2.  Extrapolation and interpolation strategies for efficiently estimating structural observables as a function of temperature and density.

Authors:  Jacob I Monroe; Harold W Hatch; Nathan A Mahynski; M Scott Shell; Vincent K Shen
Journal:  J Chem Phys       Date:  2020-10-14       Impact factor: 3.488

3.  Opening of smaller toxin pores by lipid micelle formation.

Authors:  Rajat Desikan; Pranesh Padmanabhan; K Ganapathy Ayappa
Journal:  Proc Natl Acad Sci U S A       Date:  2020-02-25       Impact factor: 11.205

4.  In silico characterization, docking, and simulations to understand host-pathogen interactions in an effort to enhance crop production in date palms.

Authors:  Meshari Alazmi; N Alshammari; Naimah A Alanazi; Abdel Moneim E Sulieman
Journal:  J Mol Model       Date:  2021-11-03       Impact factor: 1.810

5.  Activation and selectivity of OTUB-1 and OTUB-2 deubiquitinylases.

Authors:  Dakshinamurthy Sivakumar; Vikash Kumar; Michael Naumann; Matthias Stein
Journal:  J Biol Chem       Date:  2020-04-07       Impact factor: 5.157

6.  Mechanism of membrane-tethered mitochondrial protein synthesis.

Authors:  Yuzuru Itoh; Juni Andréll; Austin Choi; Uwe Richter; Priyanka Maiti; Robert B Best; Antoni Barrientos; Brendan J Battersby; Alexey Amunts
Journal:  Science       Date:  2021-02-19       Impact factor: 47.728

7.  Effects of the N-terminal dynamics on the conformational states of human dopamine transporter.

Authors:  Liang Xu; Liao Y Chen
Journal:  Biophys Chem       Date:  2022-01-25       Impact factor: 2.352

8.  Ion-dependent protein-surface interactions from intrinsic solvent response.

Authors:  Jesse L Prelesnik; Robert G Alberstein; Shuai Zhang; Harley Pyles; David Baker; Jim Pfaendtner; James J De Yoreo; F Akif Tezcan; Richard C Remsing; Christopher J Mundy
Journal:  Proc Natl Acad Sci U S A       Date:  2021-06-29       Impact factor: 11.205

9.  Generalizing the Discrete Gibbs Sampler-Based λ-Dynamics Approach for Multisite Sampling of Many Ligands.

Authors:  Jonah Z Vilseck; Xinqiang Ding; Ryan L Hayes; Charles L Brooks
Journal:  J Chem Theory Comput       Date:  2021-06-08       Impact factor: 6.006

10.  Hybrid resolution molecular dynamics simulations of amyloid proteins interacting with membranes.

Authors:  Mohtadin Hashemi; Yuri L Lyubchenko
Journal:  Methods       Date:  2021-03-13       Impact factor: 3.608

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