Biologically Inspired Algorithms Applied in Automatic Tuning of Parallel Solver Parameters for Fast Execution Times

In this paper, we present a way how to automatically find and set an optimal configuration for a linear system solver during a transient analysis in order to reduce computation time. Our approach is based on biologically inspired algorithms which are able to find a reasonable configuration in tens of trials, i.e., tens of timesteps in terminology of the transient analysis. This work shows a measurement within which we compared several optimization algorithms and explored their time overhead. We focus on parallel multiphysical solvers for engineering simulations developed for high-performance computing. Our experiment includes one such solver based on Finite Element Tearing and Interconnection and 4 test cases, but our solution is modular, thus, it can be connected to other similar solvers.