Leonardo Romor

Projects

Performance-driven refactoring of Potts associative memory network model.

Students: 

Leonardo Romor

Neural networks simulations have always been a complex computational chal- lenge because of the requirements of large amount of computational and memory resources. Due to the nature of the problem, a high performance computing approach becomes vital, because the dynamics often involves the update of a large network for a large number of time steps. Moreover, the parameter space can be fairly large. An advanced optimization for the single time step is therefore necessary, as well as a strategy to explore the parameter space in an automatic fashion.