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Efficient solid state NMR powder simulations using SMP and MPP parallel computation.

Jørgen Holm Kristensen1, Ian Farnan

  • 1Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge, CB2 3EQ, UK. jhk28@cam.ac.uk

Journal of Magnetic Resonance (San Diego, Calif. : 1997)
|April 26, 2003
PubMed
Summary

Parallel computing methods for solid-state Nuclear Magnetic Resonance (NMR) powder spectra simulations are efficient on supercomputers. Both shared and distributed memory approaches achieve high speedups, enabling advanced simulations.

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Area of Science:

  • Computational Chemistry
  • Solid-State Nuclear Magnetic Resonance (NMR) Spectroscopy
  • High-Performance Computing

Background:

  • Solid-state NMR powder spectra simulations are crucial for material characterization.
  • Efficient computational methods are needed for complex NMR spectra analysis.
  • Parallel computing offers potential for accelerating these simulations.

Purpose of the Study:

  • To present and evaluate methods for parallel simulation of solid-state NMR powder spectra.
  • To compare the performance of shared and distributed memory parallel architectures.
  • To assess the feasibility of advanced powder simulations using parallel computation.

Main Methods:

  • Implementation of OpenMP for shared memory parallel supercomputers.

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  • Development of MPI-based message passing for distributed memory parallel supercomputers.
  • Performance evaluation focusing on speedup and scalability.

    • Main Results:

    • Shared memory parallel programming (OpenMP) presents challenges due to data locality and cache effects.
    • Distributed memory parallel programming (MPI) demonstrates high efficiency.
    • Both parallel approaches achieve near-perfect application speedup.

    Conclusions:

    • Parallel computation is highly effective for solid-state NMR powder spectra simulations.
    • Both shared and distributed memory models are suitable for advanced simulations.
    • High-performance computing significantly enhances the capabilities of NMR spectral analysis.