Algorithmic and numerical techniques for atomistic modeling

Hasan Metin Aktulga, Purdue University


Molecular dynamics (MD) modeling has provided a powerful tool for simulating and understanding diverse systems – ranging from materials processes to biophysical phenomena. Many instances of this class of methods rely on a static bond structure for molecules, rendering them infeasible for reactive systems. Recent work on reactive force fields has resulted in the development of ReaxFF, a novel bond order potential that bridges quantum-scale and classical MD approaches by explicitly modeling bond activity (reactions) and charge equilibration. These aspects of ReaxFF pose significant challenges from a computational standpoint, both in sequential and parallel contexts. Evolving bond structure requires efficient dynamic data structures. Minimizing electrostatic energy through charge equilibration requires the solution of a large sparse linear system with a shielded electrostatic kernel at each sub-femtosecond long timestep. In this context, reaching spatio-temporal scales of tens of nanometers and nanoseconds, where phenomena of interest can be observed, poses significant challenges. In this thesis, first we present the design and implementation details of a sequential ReaxFF realization, sPuReMD (serial Purdue Reactive Molecular Dynamics) code. sPuReMD incorporates efficient dynamic data structures, algorithmic optimizations, numerical techinques and effective linear solvers to achieve excellent per-timestep time, linear time scaling in system size, and a low memory footprint. Upon the sPuReMD platform, we build our parallel reactive MD code, PuReMD. PuReMD inherits the highly desirable features of sPuReMD and through use of scalable parallel algorithms, it extends current spatio-temporal simulation capability for reactive atomistic systems by over an order of magnitude. PuReMD is comprehensively validated for performance and accuracy on up to 3K cores on a commodity cluster (DoE/LLNL/Hera). Potential performance bottlenecks to scalability beyond our experiments have also been analyzed. PuReMD is available over the public domain and has been used to model diverse systems ranging from strain relaxation in Si/Ge/Si nanobars, water-silica surface interaction, and oxidative stress in lipid bilayers (biomembranes).




Grama, Purdue University.

Subject Area

Computer science

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