1.4.0

• Modernize cmake build system.
  Provide VexCL::OpenCL, VexCL::Compute, VexCL::CUDA, VexCL::JIT
  imported targets, so that users may just

  add_executable(myprogram myprogram.cpp)
  target_link_libraries(myprogram VexCL::OpenCL)
  

  to build a program using the corresponding VexCL backend.
  Also stop polluting global cmake namespace with things like
  add_definitions(), include_directories(), etc.
  See http://vexcl.readthedocs.io/en/latest/cmake.html.
• Make vex::backend::kernel::config() return reference to the kernel. So
  that it is possible to config and launch the kernel in a single line:
  K.config(nblocks, nthreads)(queue, prm1, prm2, prm3);.
• Implement vector<T>::reinterpret<U>() method. It returns a new vector that
  reinterprets the same data (no copies are made) as the new type.
• Implemented new backend: JIT. The backend generates and compiles at runtime
  C++ kernels with OpenMP support. The code will not be more effective that
  hand-written OpenMP code, but allows to easily debug the generated code with
  host-side debugger. The backend also may be used to develop and test new code
  when other backends are not available.
• Let VEX_CONSTANTS to be casted to their values in the host code. So that a
  constant defined with VEX_CONSTANT(name, expr) could be used in host code
  as name. Constants are still useable in vector expressions as name().
• Allow passing generated kernel args for each GPU (#202).
  Kernel args packed into std::vector will be unpacked and passed
  to the generated kernels on respective devices.
• Reimplemented vex::SpMat as vex::sparse::ell, vex::sparse::crs,
  vex::sparse::matrix (automatically chooses one of the two formats based on
  the current compute device), and vex::sparse::distributed<format> (this one
  may span several compute devices). The new matrix-vector products are now
  normal vector expressions, while the old vex::SpMat could only be used in
  additive expressions. The old implementation is still available.
  vex::sparse::ell is now converted from host-side CRS format on compute
  device, which makes the conversion faster.
• Bug fixes and minor improvements.