  With steadily increasing parallelism for high-performance architectures,
simulations requiring a good strong scalability are prone to be limited in
scalability with standard spatial-decomposition strategies at a certain amount
of parallel processors. This can be a show-stopper if the simulation results
have to be computed with wallclock time restrictions (e.g.\,for weather
forecasts) or as fast as possible (e.g. for urgent computing). Here, the
time-dimension is the only one left for parallelization and we focus on
Parareal as one particular parallelization-in-time method.
  We discuss a software approach for making Parareal parallelization
transparent for application developers, hence allowing fast prototyping for
Parareal. Further, we introduce a decentralized Parareal which results in
autonomous simulation instances which only require communicating with the
previous and next simulation instances, hence with strong locality for
communication. This concept is evaluated by a prototypical solver for the
rotational shallow-water equations which we use as a representative black-box
solver.
