We developed an out-of-core (OC) implementation of the parallel multilevel fast multipole algorithm (MLFMA) to solve electromagnetic problems with reduced memory. The main purpose of the OC method is to reduce in-core memory (primary storage) by using mass storage (secondary storage) units. Depending on the OC implementation, the in-core data may be left in one piece or divided into partitions. If the latter, the partitions are written out into mass storage unit(s) and read into in-core memory when required. In this way, memory reduction is achieved. However, the proposed method causes time delays because reading and writing large data using massive storage units is a long procedure. In our case, repetitive access to data partitions from the mass storage increases the total time of the iterative solution part of MLFMA. Such time delays can be minimized by selecting the right data type and optimizing the sizes of the data partitions. We run the optimization tests on different types of mass storage devices, such as hard disks and solid state drives. This thesis explores OC implementation of the parallel MLFMA. To be more precise, it presents the results of optimization tests done on different partition sizes and shows how computation time is minimized despite the time delays. This thesis also presents full-wave solutions of scattering problems including hundreds of millions of unknowns by employing an OC-implemented parallel MLFMA.