The full implementation of the code is included.
The choice of the optimization method is crucial for the successful implementation of the code.
Current implementation of the code using MATLAB on a 2.3 GHz Intel Core i7 processor takes under 0.1 second per cell.
Moreover, a trained neural network gives the results significantly more quickly than a computer implementation of the code.
In this version we have restructured the serial implementation of the code so as to achieve optimal task-based parallelization.
This release presents a re-engineered implementation of the code using the new MATLAB object-oriented programming.
Derivatives of the algebraic implementation of the code and numerical testing on a hypothetical problem are used to perform the analysis.
The complete implementation of the code is based on the construction characteristics with the validation of the results obtained by benchmarking the experimental and operational data reported in the reactor Fist Criticality Final Report.
We describe our implementation of the code, that builds on previous experience made on other (simpler) many-core processors and GPUs, present benchmark results and measure performances, and finally compare with the results obtained by previous implementations developed on state-of-the-art classic multi-core CPUs and GP-GPUs.
The implementation of the code has been critically validated by a lot of evaluations and tests on a broad class of materials including two-dimensional and three-dimensional materials, providing its efficiency and capability for high-throughput screening of specific materials with targeted mechanical properties.
We give a detailed description of the features and implementation of the code and demonstrate its scaling behavior and parallel performance with a simple one-dimensional A B C lattice KMC model and a more complex three-dimensional lattice KMC model of oxygen-vacancy diffusion in a fluorite structured metal oxide.
