A derivation and scalable implementation of the synchronous parallel kinetic Monte Carlo method for simulating long-time dynamics

• Published in: Computer physics communications 2017-10, Vol.219 (C), p.246-254
• Main Authors: Byun, Hye Suk, El-Naggar, Mohamed Y., Kalia, Rajiv K., Nakano, Aiichiro, Vashishta, Priya
• Format: Article
• Language: English
• Subjects: Divide-and-conquer algorithm; Kinetic Monte Carlo simulation; MATHEMATICS AND COMPUTING; Parallel computing
• ISSN: 0010-4655; 1879-2944
• DOI: 10.1016/j.cpc.2017.05.028

Kinetic Monte Carlo (KMC) simulations are used to study long-time dynamics of a wide variety of systems. Unfortunately, the conventional KMC algorithm is not scalable to larger systems, since its time scale is inversely proportional to the simulated system size. A promising approach to resolving this issue is the synchronous parallel KMC (SPKMC) algorithm, which makes the time scale size-independent. This paper introduces a formal derivation of the SPKMC algorithm based on local transition-state and time-dependent Hartree approximations, as well as its scalable parallel implementation based on a dual linked-list cell method. The resulting algorithm has achieved a weak-scaling parallel efficiency of 0.935 on 1024 Intel Xeon processors for simulating biological electron transfer dynamics in a 4.2 billion-heme system, as well as decent strong-scaling parallel efficiency. The parallel code has been used to simulate a lattice of cytochrome complexes on a bacterial-membrane nanowire, and it is broadly applicable to other problems such as computational synthesis of new materials.