Speaker
Description
Modeling thermal properties of new materials using computational methods based on Quantum Mechanics usually provides us with a well-defined ground state of the system, but not its transitional temperatures. For obtaining these properties, we propose a generic and high-performance method for mapping an ab-initio system onto the Heisenberg model using our original code (github.com/Mellechowicz/JorG).
The most crucial part of the algorithm is identifying a set of metastable states of the system, which is achieved through simulated annealing of a ferromagnetic 3D Ising model. This being also the most resource-intensive part of the algorithm, parallelizing it would significantly accelerate the entire process.
To accomplish this, we intend to implement parallel simulated annealing utilizing both distributed (Message Passing Interface) and shared (OpenMP/OpenACC) memory models. In this way, we will provide researchers with a fast and automatic scheme for assessing transitional temperatures that is well-adjusted for running in parallel on supercomputers, accelerating the design of new materials.
