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MOLDY

MOLDY is a highly portable and parallelized molecular dynamics package under GNU General Public License. It handles pairwise central force models, point-charge electrostatics, and Newton-Euler equations of rotational dynamics. The Ewald Sum technique efficiently sums interactions between ions and periodic images. Long-ranged forces are managed using cancelling distributions in reciprocal space for accurate energy calculations. The parallelization is achieved through a "Replicated data" approach, offering simplicity, load-balancing, and efficient performance for small to medium-sized systems. However, it may not scale well to very large processor numbers.

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MOLDY

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  1. MOLDY CEC Inha University Chi-Ok Hwang

  2. MOLDY • General molecular dynamics (MD) package • GNU general public license • highly portable • parallelized • Only pairwise central force models and point-charge electrostatics • Newton-Euler equations of rotational dynamics

  3. Handling Long-ranged Forces: Ewald Sum • Technique for efficiently summing the interaction between an ion and all its periodic images • Each point charge surrounded by a charge distribution of equal magnitude opposite sign with a Gaussian distribution • Cancelling distribution; charge distribution of the same sign as the original charge and the same shape

  4. Handling Long-ranged Forces: Ewald Sum • Cancelling distribution summed in reciprocal space • Final potential energy = real space sum + reciprocal space sum – (self_term + surface term)

  5. MOLDY input

  6. MOLDY input

  7. MOLDY input: Example

  8. MOLDY input

  9. MOLDY input

  10. MOLDY input: Example

  11. MOLDY input

  12. MOLDY input

  13. MOLDY input: Example

  14. MOLDY output

  15. Parallelization • “Replicated data” approach - each processor maintaining a complete set of dynamical variable arrays for all particles; short-ranged and reciprocal-space force calculations are divided among the processors - simplicity of programming - straightforward load-balancing - coarse communication granularity - efficient for small and medium-sized systems - poor scaling to very large numbers of processors

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