Within this project, we aim to significantly push the boundaries of size restrictions and simulation speed by introducing algorithms that are particularly suited for distributed computations and by relying on software frameworks that a specialized on the handling of large amounts of data. Namely, we will implement the parallel-in-time integration scheme parareal which has already proved to lead to significant computational speedups in other scientific disciplines. In another subproject we will exploit the capabilities of modern finite-element libraries to implement a distributed higher-order micromagnetic code suited for high-performance computational clusters. In the third subproject, we will use the highly optimized tensor library TensorFlow to implement a novel finite-difference formulation to be solved on graphics processing units. This novel formulation will allow for the rigorous and accurate description of composite materials which will be particularly beneficial for the simulation of granular media as used in numerous magnetic applications. Combining the findings of the individual subprojects will lead to further performance enhancements.