This restructuring allows for easier separation of modules into
separate repositories later. Also, now pip install with repo url can be
used.

The setup.py files have also been updated to correctly reference each
other. Module versions are not extracted from git state

- small (length < 5) arrays with shape and stride information had to be
  memcpy'd to the GPU before every kernel call
- instead of passing the information as arrays, the single elements are
  passed
- leads to more function arguments, but simplifies GPU kernel calls

-> changes in all backends required

- bugfix in vector-typing of piecewise functions
- cast_function is now a sympy atom - fixes problems with sympy > 1.1
- replace_inner_stride_with_one is a bit faster now

- support aligned load/stores
- nontemporal stores
- aligned memory allocation for arrays and temporary buffers

- vectorization for loops with ranges that are not a multiple of vector width
- vectorization for variable sized loops if special transformation
  replace_inner_stride_with_one is run

- flags can be force when setting boundaries, this is helpful for:
- setting up quantities (e.g. relaxation rate..) dependent on current
  flag configuration
- bit operation fix when pickling: function has to have the same name
  as the python object

- test run again
- notebooks not yet

- single function to create kernel for specified target
- data type creation from string - reuse numpy functionality
- bugfixes in dot display

- alignment of index array when using additional data
- data types have been hashed incorrectly

- support for logical operators, and/or
- both phase field kernels can be vectorized now

- phasefield phi sweep vectorizes successfully

Added LLVM: CodePrinter and a compiler
Updated data_types
Added tests
Added jupyter notebooks
Fixed bugs
Restructured transformation functions

- renaming because of clashes with types.py from other packages

- sympys piecewise defined functions are mapped to blend instructions
- cast function is now a class
- several bugfixes

- first vectorization tests are running
- type system: use memoized getTypeOfExpression
- casts are done using sp.Function('cast')
- C backend adapted for vectorization support
- AST nodes can required optional headers

- support for kernels that run over walberla ghost layers

- pystencils can create now a non-compilable kernel that can be
  analyzed by kerncraft

- this extension is necessary for more generic boundary treatment
- cells can now be structs, i.e. contain different data types
- instead of having numeric index dimensions, one can use the index per cell to adress struct elements

- use data type class consistently instead of strings (in TypedSymbol, Field and jit module)
- new datatype class is based on numpy types with additional specifier information (const and restrict)
- translation between data type class and other modules (numpy, ctypes)