  Magnetic gels are soft elastic materials consisting of magnetic particles
embedded in a polymer network. Their shape and elasticity can be controlled by
an external magnetic field, which gives rise to both, engineering and
biomedical applications. Computer simulations are a commonly used tool to study
these materials. A well-known bottleneck of these simulations is the demanding
calculation of dipolar interactions. Under periodic boundary conditions
established algorithms are available for doing this, however, at the expense of
restricting the way in which the gels can deform in an external magnetic field.
Moreover, the magnetic properties depend on the sample shape, ruling out
periodic boundary conditions entirely for some research questions. In this
article we will employ the recently developed dipolar variant of the P$^2$NFFT
method that is able to calculate dipolar interactions under open boundary
conditions with an $N \log N$ scaling in the number of particles, rather than
the expensive $N^2$ scaling of a direct summation of pair forces. The dipolar
P$^2$NFFT method has been implemented within the ScaFaCoS library. The
molecular dynamics software ESPResSo has been extended to make use of the
library.
  After a short summary of the method, we will discuss its value for studying
magnetic soft matter systems. A particular focus is put on developing a tuning
strategy to reach the best performance of the method at a predefined accuracy,
and lastly applying the method to a magnetic gel model. Here, adapting to the
gel's change in shape during the course of a simulation is of particular
interest.
