Literature DB >> 23264758

Revisiting Molecular Dynamics on a CPU/GPU system: Water Kernel and SHAKE Parallelization.

A Peter Ruymgaart1, Ron Elber.   

Abstract

We report Graphics Processing Unit (GPU) and Open-MP parallel implementations of water-specific force calculations and of bond constraints for use in Molecular Dynamics simulations. We focus on a typical laboratory computing-environment in which a CPU with a few cores is attached to a GPU. We discuss in detail the design of the code and we illustrate performance comparable to highly optimized codes such as GROMACS. Beside speed our code shows excellent energy conservation. Utilization of water-specific lists allows the efficient calculations of non-bonded interactions that include water molecules and results in a speed-up factor of more than 40 on the GPU compared to code optimized on a single CPU core for systems larger than 20,000 atoms. This is up four-fold from a factor of 10 reported in our initial GPU implementation that did not include a water-specific code. Another optimization is the implementation of constrained dynamics entirely on the GPU. The routine, which enforces constraints of all bonds, runs in parallel on multiple Open-MP cores or entirely on the GPU. It is based on Conjugate Gradient solution of the Lagrange multipliers (CG SHAKE). The GPU implementation is partially in double precision and requires no communication with the CPU during the execution of the SHAKE algorithm. The (parallel) implementation of SHAKE allows an increase of the time step to 2.0fs while maintaining excellent energy conservation. Interestingly, CG SHAKE is faster than the usual bond relaxation algorithm even on a single core if high accuracy is expected. The significant speedup of the optimized components transfers the computational bottleneck of the MD calculation to the reciprocal part of Particle Mesh Ewald (PME).

Entities:  

Year:  2012        PMID: 23264758      PMCID: PMC3524996          DOI: 10.1021/ct300324k

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


  14 in total

1.  Computing time scales from reaction coordinates by milestoning.

Authors:  Anton K Faradjian; Ron Elber
Journal:  J Chem Phys       Date:  2004-06-15       Impact factor: 3.488

2.  Scalable molecular dynamics with NAMD.

Authors:  James C Phillips; Rosemary Braun; Wei Wang; James Gumbart; Emad Tajkhorshid; Elizabeth Villa; Christophe Chipot; Robert D Skeel; Laxmikant Kalé; Klaus Schulten
Journal:  J Comput Chem       Date:  2005-12       Impact factor: 3.376

3.  Extending molecular dynamics time scales with milestoning: example of complex kinetics in a solvated peptide.

Authors:  Anthony M A West; Ron Elber; David Shalloway
Journal:  J Chem Phys       Date:  2007-04-14       Impact factor: 3.488

4.  SHAKE parallelization.

Authors:  Ron Elber; A Peter Ruymgaart; Berk Hess
Journal:  Eur Phys J Spec Top       Date:  2011-11-01       Impact factor: 2.707

5.  Milestoning without a Reaction Coordinate.

Authors:  Peter Májek; Ron Elber
Journal:  J Chem Theory Comput       Date:  2010       Impact factor: 6.006

6.  CCMA: A Robust, Parallelizable Constraint Method for Molecular Simulations.

Authors:  Peter Eastman; Vijay S Pande
Journal:  J Chem Theory Comput       Date:  2010-02-09       Impact factor: 6.006

7.  Revisiting and computing reaction coordinates with Directional Milestoning.

Authors:  Serdal Kirmizialtin; Ron Elber
Journal:  J Phys Chem A       Date:  2011-04-18       Impact factor: 2.781

8.  How conformational dynamics of DNA polymerase select correct substrates: experiments and simulations.

Authors:  Serdal Kirmizialtin; Virginia Nguyen; Kenneth A Johnson; Ron Elber
Journal:  Structure       Date:  2012-04-03       Impact factor: 5.006

9.  MOIL-opt: Energy-Conserving Molecular Dynamics on a GPU/CPU system.

Authors:  A Peter Ruymgaart; Alfredo E Cardenas; Ron Elber
Journal:  J Chem Theory Comput       Date:  2011-08-26       Impact factor: 6.006

10.  Efficient nonbonded interactions for molecular dynamics on a graphics processing unit.

Authors:  Peter Eastman; Vijay S Pande
Journal:  J Comput Chem       Date:  2010-04-30       Impact factor: 3.376

View more
  7 in total

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Authors:  Ron Elber
Journal:  J Chem Phys       Date:  2016-02-14       Impact factor: 3.488

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Authors:  Mauro L Mugnai; Yue Shi; Adrian T Keatinge-Clay; Ron Elber
Journal:  Biochemistry       Date:  2015-04-02       Impact factor: 3.162

3.  Extracting intrinsic dynamic parameters of biomolecular folding from single-molecule force spectroscopy experiments.

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4.  Automated Optimization of Potential Parameters.

Authors:  Di Pierro Michele; Elber Ron
Journal:  J Chem Theory Comput       Date:  2013-08-13       Impact factor: 6.006

5.  Partition of Positively and Negatively Charged Tryptophan Ions in Membranes with Inverted Phospholipid Heads: Simulations and Experiments.

Authors:  Alfredo E Cardenas; Cari M Anderson; Ron Elber; Lauren J Webb
Journal:  J Phys Chem B       Date:  2019-04-09       Impact factor: 2.991

6.  A small-molecule Skp1 inhibitor elicits cell death by p53-dependent mechanism.

Authors:  Muzammal Hussain; Yongzhi Lu; Muqddas Tariq; Hao Jiang; Yahai Shu; Shuang Luo; Qiang Zhu; Jiancun Zhang; Jinsong Liu
Journal:  iScience       Date:  2022-06-14

7.  Accelerated Molecular Mechanical and Solvation Energetics on Multicore CPUs and Manycore GPUs.

Authors:  Deukhyun Cha; Alexander Rand; Qin Zhang; Rezaul A Chowdhury; Jesmin Jahan Tithi; Chandrajit Bajaj
Journal:  ACM BCB       Date:  2015-09
  7 in total

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