-> by default sympy generates "fmin" C-function for sp.Min which
   is wrong for integer parameters

- 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

- constants are typed - no need any more for this parameter

- 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

- removed warnings
- added flake8 as CI target

- test run again
- notebooks not yet

- in-kernel Neumann boundaries
- flag-interface for boundary handling makes one flag field multiple
  boundary handlings possible
- generator: support for bitwise logical operators

- step class for LB phasefield generic enough to work with 3-phase and
  N-phase models
- cahn hilliard can either be solved by LBM or by finite differences
- 3 phase model can be solved with rho phase or without

- loop cutting
- simplification of conditionals inside loop

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

- phasefield phi sweep vectorizes successfully

- activated vectorization for LBM kernels

- 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

- abstraction layer for selecting CUDA block and grid sizes
  - line based (was implemented before)
  - block based (new, more flexible)
-  new conditional (if/else) ast node, which is necessary for indexing schemes (guarding if)

- 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)

- windows support
- automatic caching and creation of shared library with all generated kernels
- restrict keyword and function prefixes are preprocessor macros now -> easier to generate one code for linux, cuda, windows