use the general classes instead. they support levelwise load
balancing via a constructor parameter

default is levelwise for backward compatibility

- allows for nested execution flow (i.e. solver loop inside time loop)
- timing tree integration
- parallel CUDA stream support

- WALBERLA_BUILD_WITH_OPENMP was never defined

- information from CMake to codegen: double/float, OpenMP, ...

- comparison to old CPU transfer communication included

previously the ghost layer was aligned

Features:
   - uses generated pack infos for packing & unpacking directly on GPU
   - can directly send GPU buffers if cuda-enabled MPI is available,
     otherwise the packed buffers are transfered to CPU first
   - communication hiding with cuda streams: communication can be run
     asynchronously - especially useful when compute kernel is also
     split up into inner and outer part

- added RAII classes for CUDA streams and events
- equivalence test that checks if generated CPU and GPU (overlapped)
  versions are computing same result as normal waLBerla LBM kernel

added filter to exclude external libraries