Opencl datahandling

Since the target_dh_refactoring was never merged, we decided to do the refactoring at smaller steps and recover the original OpenCL datahandling PR.

Refactoring to merge target and backend can be done later.

pystencils/datahandling/serial_datahandling.py

@@ -23,6 +23,7 @@ class SerialDataHandling(DataHandling):
                  periodicity: Union[bool, Sequence[bool]] = False,
                  default_target: str = 'cpu',
                  opencl_queue=None,
+                 opencl_ctx=None,
                  array_handler=None) -> None:
         """
         Creates a data handling for single node simulations.
@@ -44,6 +45,8 @@ class SerialDataHandling(DataHandling):
         self.custom_data_cpu = DotDict()
         self.custom_data_gpu = DotDict()
         self._custom_data_transfer_functions = {}
+        self._opencl_queue = opencl_queue
+        self._opencl_ctx = opencl_ctx
 
         if array_handler:
             self.array_handler = array_handler
@@ -315,11 +318,15 @@ class SerialDataHandling(DataHandling):
                     result.append(get_periodic_boundary_functor(filtered_stencil, ghost_layers=gls))
                 else:
                     from pystencils.gpucuda.periodicity import get_periodic_boundary_functor as boundary_func
+                    target = 'gpu' if not isinstance(self.array_handler, PyOpenClArrayHandler) else 'opencl'
                     result.append(boundary_func(filtered_stencil, self._domainSize,
                                                 index_dimensions=self.fields[name].index_dimensions,
                                                 index_dim_shape=values_per_cell,
                                                 dtype=self.fields[name].dtype.numpy_dtype,
-                                                ghost_layers=gls))
+                                                ghost_layers=gls,
+                                                target=target,
+                                                opencl_queue=self._opencl_queue,
+                                                opencl_ctx=self._opencl_ctx))
 
         if target == 'cpu':
             def result_functor():