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Molecular Dynamics Simulations

MASSIVELY PARALLEL CODE FOR MULTISCALE MOLECULAR DYNAMICS (MD) SIMULATIONS

LEAD PI: DR. DAVIDE MANDELLI

CO PI: DR. PAOLO CARLONI

This collaborative project aims at the further development of our existing massively parallel code for multiscale molecular dynamics (MD) simulations, MiMiC.1,2 The candidate will work on the implementation of a free-energy approach, based on classical path-integrals, that allows to sample directly from the space of trajectories.3 The algorithm will be implemented using a multireplica approach able to take full advantage of massively parallel HPC facilities. 

The expected outcome of this project is a new software module for our open-source package. Successful implementation may lead to a publication in a high-impact journal.

This collaboration will be part of a long-term project connected to the development of the MiMiC code. The project is going to be supported in the future through multiple initiatives and grants within the MiMiC consortium. Therefore, this opens opportunities for further longer collaborations with successful candidates.

REQUIRED SKILLS

Successful candidates should have:

  • Master’s in physics, chemistry or computer science
  • Knowledge of Fortran or C++
  • User-experience with Linux OS
  • Some understanding of Python 
  • Experience in HPC computing and MD computational workflows is a plus

COMPUTATIONAL RESOURCES

During the collaboration, the intern will be given access to machines located at Jülich Forschungszentrum and RWTH Aachen University IT Center. This gives a unique opportunity to get a hands-on experience with some of the novel supercomputing architectures such as the modular cluster-booster system available at JSC.

REFERENCES

  1. Haugaard Olsen J. M., Bolnykh V., Meloni S., Ippoliti E., Bircher M. P., Carloni P., and Rothlisberger U., MiMiC: A Novel Framework for Multiscale Modeling in Computational Chemistry
    Journal of Chemical Theory and Computation 2019 15 (6), 3810-3823
    DOI: 10.1021/acs.jctc.9b00093
  2. Bolnykh V., Haugaard Olsen J. M., Meloni S., Bircher M. P., Ippoliti E., Carloni P., and Rothlisberger U., Extreme Scalability of DFT-Based QM/MM MD Simulations Using MiMiC
    Journal of Chemical Theory and Computation 2019 15 (10), 5601-5613
    DOI: 10.1021/acs.jctc.9b00424
  3. Mandelli D., Hirshberg B., Parrinello M., Metaynamics of Paths, Physical Review Letters 2020 125 (2), 026001 DOI: 10.1103/PhysRevLett.125.026001