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High-Scalable Collaborated Parallel Framework for Large-Scale Molecular Dynamic Simulation on Tianhe-2 Supercomputer.

Shaoliang Peng, Xiaoyu Zhang, Wenhe Su

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |July 12, 2018
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a parallel acceleration strategy for Molecular Dynamics (MD) simulations using the Assisted Model Building with Energy Refinement (AMBER) software on the Tianhe-2 supercomputer. The optimized AMBER achieved a significant speedup for large-scale molecular simulations.

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    Area of Science:

    • Computational chemistry and physics
    • Materials science
    • Biochemistry and biophysics

    Background:

    • Molecular dynamics (MD) simulations are crucial for studying atomic and molecular movements, offering detailed microscopic insights.
    • MD simulations are increasingly used in materials science, biochemistry, and biophysics, but large-scale simulations require significant computational power.
    • The Assisted Model Building with Energy Refinement (AMBER) software is a popular tool for MD simulations, yet its performance for large systems needs enhancement.

    Purpose of the Study:

    • To develop and implement a parallel acceleration strategy for AMBER software.
    • To improve the computational efficiency of large-scale MD simulations on the Tianhe-2 supercomputer.
    • To achieve substantial speedup for microsecond-scale simulations involving millions of atoms.

    Main Methods:

    • A multi-level parallelization approach was employed for AMBER on the Tianhe-2 supercomputer.
    • Optimization included fine-grained OpenMP parallelization on single CPUs.
    • Further acceleration involved single-node CPU/MIC parallelization and multi-node, multi-MIC collaborative parallelization.

    Main Results:

    • The parallel acceleration strategy significantly enhanced AMBER's performance.
    • A speedup of 25-33 times was achieved compared to the original AMBER program.
    • The optimization effectively addressed the computational demands of large-scale, microsecond-scale MD simulations.

    Conclusions:

    • The proposed parallel acceleration strategy offers a viable solution for accelerating large-scale MD simulations.
    • The optimized AMBER on Tianhe-2 demonstrates improved efficiency for complex molecular modeling tasks.
    • This work contributes to advancing computational capabilities in molecular dynamics research.