The increasing demand for computational power in diverse scientific and engineering fields has resulted in a notable rise in parallel computing research. This is particularly evident in disciplines such as Computational Electromagnetics, which strive to develop accurate and efficient solvers for Maxwell’s equations. Given the current technological advancements that necessitate large-scale electromagnetic simulations involving billions of unknowns, distributed- memory systems have emerged as the primary solution due to their improved computation and memory capabilities. This thesis analyzes the way in which parallel computing impacts two widely used algo- rithms for electromagnetic problems: the Adaptive Cross Approximation (ACA) and the Fast Multipole Method (FMM), with a special focus on the computational and parallel execution aspects.