Scalability of DL_POLY on High Performance Computing Platform

Mabakane, Mabule Samuel; Moeketsi, D.M.; Lopis, Anton S.

doi:10.18489/sacj.v29i3.405

Cited by 4 publications

(4 citation statements)

References 17 publications

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“…The reason that DL_FFLUX scales worse than DL_POLY in the L ′ = 0 case is once again due to the redundant work when predicting point charges. Note that the scalability of the MPI in various versions of DL_POLY has been tested extensively in the past. , …”

Section: Resultsmentioning

confidence: 99%

“…Note that the scalability of the MPI in various versions of DL_POLY has been tested extensively in the past. 56,57 Profiling also gives us some insight into the percentage of the total runtime spent in DL_FFLUX and DL_POLY routines (as well as MPI-specific routines), which is presented in Figure 16 as pie charts. For the sake of clarity, just the profiles for N p = 1, 8, and 36 are shown; the rest of the pie charts appear in Figure S9 as well as a more detailed "sample" breakdown in Figure S10 showing the relative timings of the top 5 most costly subroutines.…”

Section: Resultsmentioning

confidence: 99%

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DL_FFLUX: A Parallel, Quantum Chemical Topology Force Field

Symons

Bane

Popelier

2021

J. Chem. Theory Comput.

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DL_FFLUX is a force field based on quantum chemical topology that can perform molecular dynamics for flexible molecules endowed with polarizable atomic multipole moments (up to hexadecapole). Using the machine learning method kriging (aka Gaussian process regression), DL_FFLUX has access to atomic properties (energy, charge, dipole moment, etc.) with quantum mechanical accuracy. Newly optimized and parallelized using domain decomposition Message Passing Interface (MPI), DL_FFLUX is now able to deliver this rigorous methodology at scale while still in reasonable time frames. DL_FFLUX is delivered as an add-on to the widely distributed molecular dynamics code DL_POLY 4.08. For the systems studied here (10 3 − 10 5 atoms), DL_FFLUX is shown to add minimal computational cost to the standard DL_POLY package. In fact, the optimization of the electrostatics in DL_FFLUX means that, when high-rank multipole moments are enabled, DL_FFLUX is up to 1.25× faster than standard DL_POLY. The parallel DL_FFLUX preserves the quality of the scaling of MPI implementation in standard DL_POLY. For the first time, it is feasible to use the full capability of DL_FFLUX to study systems that are large enough to be of real-world interest. For example, a fully flexible, high-rank polarized (up to and including quadrupole moments) 1 ns simulation of a system of 10 125 atoms (3375 water molecules) takes 30 h (wall time) on 18 cores.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

DL_FFLUX: A Parallel, Quantum Chemical Topology Force Field

Symons

Bane

Popelier

2021

J. Chem. Theory Comput.

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“…Other work relating to the benchmarking of molecular dynamics simulations to assess the performance of various popular MD software programmes, including DL_POLY, can be found in references [51][52][53][54].…”

Section: Dl_poly 3 and Dl_polymentioning

confidence: 99%

DL_POLY - A performance overview analysing, understanding and exploiting available HPC technology

Guest

Elena

Chalk

2019

Molecular Simulation

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This paper considers the performance attributes of the molecular simulation code, DL_POLY, as measured and analysed over the past two decades. Following a brief overview of HPC technology, and the performance improvements over that period, we define the benchmark casesfor both DL_POLY Classic and DL_POLY 3 & 4used in generating a broad overview of performance across well over 100 HPC systems, from the Cray T3E/1200 to today's Intel Skylake clusters and accelerator technology offerings from Intel's Xeon Phi co-processor family. Consideration is given to the tools that have proved helpful in analysing the code's performance. With a more rigorous analysis of performance on recent systems, we discuss the optimum choice of processor and interconnect, and present power measurements when running the code, comparing these to measurements for other community codes.

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“…The reason that DL_FFLUX scales worse than DL_POLY in the L'=0 case is once again due to the redundant work when predicting point charges. Note that the scalability of the MPI in various versions of DL_POLY has been tested extensively in the past55,56 .…”

mentioning

confidence: 99%

DL_FFLUX: a parallel, quantum chemical topology force field

Symons

Bane

Popelier

2021

Preprint

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DL_FFLUX performs molecular dynamics for flexible molecules endowed with polarisable QTAIM atomic multipole moments, predicted by the machine learning method Gaussian Process Regression. Newly optimised and parallelised using domain-decomposition MPI, DL_FFLUX now operates in reasonable time frames. DL_FFLUX is delivered as an add-on to the widely distributed molecular dynamics code DL_POLY 4.08. For the systems studied here (10**3-10**5 atoms), DL_FFLUX adds minimal computational cost to the standard DL_POLY package. The parallel DL_FFLUX preserves the quality of the scaling of the MPI implementation in standard DL_POLY. For the first time it is feasible to use the full capability of DL_FFLUX to study systems that are large enough to be of real world interest. For example, a fully flexible, high-rank polarised (up to and including quadrupole moments) 1 ns simulation of a system of 10,125 atoms (3,375 water molecules) takes 30 hours (wall time) on 18 cores.

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Scalability of DL_POLY on High Performance Computing Platform

Cited by 4 publications

References 17 publications

DL_FFLUX: A Parallel, Quantum Chemical Topology Force Field

DL_FFLUX: A Parallel, Quantum Chemical Topology Force Field

DL_POLY - A performance overview analysing, understanding and exploiting available HPC technology

DL_FFLUX: a parallel, quantum chemical topology force field

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