Exact distributed kinetic Monte Carlo simulations for on-lattice chemical kinetics: lessons learnt from medium- and large-scale benchmarks.

Kinetic Monte Carlo (KMC) simulations have been instrumental in multiscale catalysis studies, enabling the elucidation of the complex dynamics of heterogeneous catalysts and the prediction of macroscopic performance metrics, such as activity and selectivity. However, the accessible length- and time-scales have been a limiting factor in such simulations. For instance, handling lattices containing millions of sites with 'traditional' sequential KMC implementations is prohibitive owing to large memory requirements and long simulation times. We have recently established an approach for exact, distributed, lattice-based simulations of catalytic kinetics which couples the Time-Warp algorithm with the Graph-Theoretical KMC framework, enabling the handling of complex adsorbate lateral interactions and reaction events within large lattices. In this work, we develop a lattice-based variant of the Brusselator system, a prototype chemical oscillator pioneered by Prigogine and Lefever in the late 60s, to benchmark and demonstrate our approach. This system can form spiral wave patterns, which would be computationally intractable with sequential KMC, while our distributed KMC approach can simulate such patterns 15 and 36 times faster with 625 and 1600 processors, respectively. The medium- and large-scale benchmarks thus conducted, demonstrate the robustness of the approach, and reveal computational bottlenecks that could be targeted in further development efforts. This article is part of a discussion meeting issue 'Supercomputing simulations of advanced materials'.

Large-scale benchmarks of the time-warp/graph-theoretical kinetic Monte Carlo approach for distributed on-lattice simulations of catalytic kinetics.

Motivated by the need to perform large-scale kinetic Monte Carlo (KMC) simulations, in the context of unravelling complex phenomena such as catalyst reconstruction and pattern formation, we extend the work of Ravipati et al. [S. Ravipati, G. D. Savva, I.-A. Christidi, R. Guichard, J. Nielsen, R. Réocreux and M. Stamatakis, Comput. Phys. Commun., 2022, 270, 108148] in benchmarking the performance of a distributed-computing, on-lattice KMC approach. The latter, implemented in our software package Zacros, combines the graph-theoretical KMC framework with the Time-Warp algorithm for parallel discrete event simulations, and entails dividing the lattice into subdomains, each assigned to a processor. The cornerstone of the Time-Warp algorithm is the state queue, to which snapshots of the simulation state are saved regularly, enabling historical KMC information to be corrected when conflicts occur at subdomain boundaries. Focusing on three model systems, we highlight the key Time-Warp parameters that can be tuned to optimise performance. The frequency of state saving, controlled by the state saving interval, δsnap, is shown to have the largest effect on performance, which favours balancing the overhead of re-simulating KMC history with that of writing state snapshots to memory. Also important is the global virtual time (GVT) computation interval, ΔτGVT, which has little direct effect on the progress of the simulation but controls how often the state queue memory can be freed up. We also find that pre-allocating memory for the state queue data structure favours performance. These findings will guide users in maximising the efficiency of Zacros or other distributed KMC software, which is a vital step towards realising accurate, meso-scale simulations of heterogeneous catalysis.

Comparison of Queueing Data-Structures for Kinetic Monte Carlo Simulations of Heterogeneous Catalysts.

On-lattice kinetic Monte Carlo (KMC) is a computational method used to simulate (among others) physicochemical processes on catalytic surfaces. The KMC algorithm propagates the system through discrete configurations by selecting (with the use of random numbers) the next elementary process to be simulated, e.g., adsorption, desorption, diffusion, or reaction. An implementation of such a selection procedure is the first-reaction method in which all realizable elementary processes are identified and assigned a random occurrence time based on their rate constant. The next event to be executed will then be the one with the minimum interarrival time. Thus, a fast and efficient algorithm for selecting the most imminent process and performing all of the necessary updates on the list of realizable processes post execution is of great importance. In the current work, we implement five data-structures to handle the elementary process queue during a KMC run: an unsorted list, a binary heap, a pairing heap, a one-way skip list, and finally, a novel two-way skip list with a mapping array specialized for KMC simulations. We also investigate the effect of compiler optimizations on the performance of these data-structures on three benchmark models, capturing CO oxidation, a simplified water gas shift mechanism, and a temperature-programmed desorption run. Excluding the least efficient and impractical for large-problems unsorted list, we observe a 3× speedup of the binary or pairing heaps (most efficient) compared to the one-way skip list (least efficient). Compiler optimizations deliver a speedup of up to 1.8×. These benchmarks provide valuable insight into the importance of, often-overlooked, implementation-related aspects of KMC simulations, such as the queueing data-structures. Our results could be particularly useful in guiding the choice of data-structures and algorithms that would minimize the computational cost of large-scale simulations.

Regional distribution of circumferential residual strains in the human aorta according to age and gender.

The biomechanical response of the human aorta varies with axial location, but little is known about the respective variation of residual strains. Such data are available for common lab animals, but in the traditional opening angle measurement the aorta is considered as an ideal cylinder and average residual strains are measured, so that the spatial variations of local residual strains are not determined. The present study provides opening angle and residual strain data throughout the course and around the circumference of the aorta harvested during autopsy. Opening angle showed notable topographical variation; the highest value was at the top of aortic arch, declining abruptly toward the ascending aorta and to a near-constant value in the descending aorta, and rising in the abdominal aorta. The variation of curvature and of external but not internal residual stretch resembled that of opening angle. Extensive residual stress and wall thickness differences were evidenced among quadrants, with the more pre-stressed being also the thicker quadrants. Gender had overall minor effects, but aging led to increased parameters, occurring earlier in the distal aorta but at later stages becoming predominant proximally. Differences in caliber were pronounced in older subjects, unlike those in opening angle, residual stretches, and thickness that were striking in middle-aged subjects. By contrast, curvature decreased with aging in relation to the smaller percentwise opening angle differences. Detailed knowledge of the zero-stress/no-load geometry of the human aortic wall is critical for an in-depth understanding of aortic physiology, while providing the basis for comparison with disease.

Unraveling the mechanisms of extreme radioresistance in prokaryotes: Lessons from nature.

The last 50 years, a variety of archaea and bacteria able to withstand extremely high doses of ionizing radiation, have been discovered. Several lines of evidence suggest a variety of mechanisms explaining the extreme radioresistance of microorganisms found usually in isolated environments on Earth. These findings are discussed thoroughly in this study. Although none of the strategies discussed here, appear to be universal against ionizing radiation, a general trend was found. There are two cellular mechanisms by which radioresistance is achieved: (a) protection of the proteome and DNA from damage induced by ionizing radiation and (b) recruitment of advanced and highly sophisticated DNA repair mechanisms, in order to reconstruct a fully functional genome. In this review, we critically discuss various protecting (antioxidant enzymes, presence or absence of certain elements, high metal ion or salt concentration etc.) and repair (Homologous Recombination, Single-Strand Annealing, Extended Synthesis-Dependent Strand Annealing) mechanisms that have been proposed to account for the extraordinary abilities of radioresistant organisms and the homologous radioresistance signature genes in these organisms. In addition, and based on structural comparative analysis of major radioresistant organisms, we suggest future directions and how humans could innately improve their resistance to radiation-induced toxicity, based on this knowledge.