Merge pull request #2470 from devitocodes/tkns

dsl: Move SubDimension thickness evaluation to the thicknesses themselves

devito/data/decomposition.py

@@ -320,7 +320,7 @@ def index_glb_to_loc(self, *args, rel=True):
             if self.loc_empty:
                 return None
             abs_ofs, side = args
-            if side is LEFT:
+            if side == LEFT:
                 rel_ofs = self.glb_min + abs_ofs - base
                 if abs_ofs >= base and abs_ofs <= top:
                     return rel_ofs

devito/ir/equations/algorithms.py

@@ -8,7 +8,7 @@
                           ConditionalDimension)
 from devito.types.array import Array
 from devito.types.basic import AbstractFunction
-from devito.types.dimension import MultiSubDimension
+from devito.types.dimension import MultiSubDimension, Thickness
 from devito.data.allocators import DataReference
 from devito.logger import warning
 
@@ -213,18 +213,24 @@ def _(expr, mapper, rebuilt, sregistry):
     _concretize_subdims(expr.implicit_dims, mapper, rebuilt, sregistry)
 
 
+@_concretize_subdims.register(Thickness)
+def _(tkn, mapper, rebuilt, sregistry):
+    if tkn in mapper:
+        # Already have a substitution for this thickness
+        return
+
+    mapper[tkn] = tkn._rebuild(name=sregistry.make_name(prefix=tkn.name))
+
+
 @_concretize_subdims.register(SubDimension)
 def _(d, mapper, rebuilt, sregistry):
     if d in mapper:
         # Already have a substitution for this dimension
         return
 
-    tkns_subs = {tkn: tkn._rebuild(name=sregistry.make_name(prefix=tkn.name))
-                 for tkn in d.tkns}
-    left, right = [mM.subs(tkns_subs) for mM in (d.symbolic_min, d.symbolic_max)]
-    thickness = tuple((v, d._thickness_map[k]) for k, v in tkns_subs.items())
-
-    mapper[d] = d._rebuild(symbolic_min=left, symbolic_max=right, thickness=thickness)
+    tkns = tuple(t._rebuild(name=sregistry.make_name(prefix=t.name)) for t in d.tkns)
+    mapper.update({tkn0: tkn1 for tkn0, tkn1 in zip(d.tkns, tkns)})
+    mapper[d] = d._rebuild(thickness=tkns)
 
 
 @_concretize_subdims.register(ConditionalDimension)
@@ -261,11 +267,9 @@ def _(d, mapper, rebuilt, sregistry):
         # Already have a substitution for this dimension
         return
 
-    abstract_tkns = MultiSubDimension._symbolic_thickness(d.parent.name)
-    concrete_tkns = tuple(tkn._rebuild(name=sregistry.make_name(prefix=tkn.name))
-                          for tkn in abstract_tkns)
-
-    kwargs = {'thickness': concrete_tkns}
+    tkns = tuple(tkn._rebuild(name=sregistry.make_name(prefix=tkn.name))
+                 for tkn in d.thickness)
+    kwargs = {'thickness': tkns}
     fkwargs = {}
 
     idim0 = d.implicit_dimension

devito/ir/support/basic.py

@@ -1376,7 +1376,7 @@ def disjoint_test(e0, e1, d, it):
     if d.is_Custom:
         subs = {}
     elif d.is_Sub and d.is_left:
-        subs = {d.root.symbolic_min: 0, **dict([d.thickness.left])}
+        subs = {d.root.symbolic_min: 0, d.ltkn: d.ltkn.value}
     else:
         return False
 

devito/mpi/halo_scheme.py

@@ -89,8 +89,7 @@ def __init__(self, exprs, ispace):
                              if d._defines & self.dimensions])
         subdims = [d for d in dims if d.is_Sub and not d.local]
         for i in subdims:
-            ltk, _ = i.thickness.left
-            rtk, _ = i.thickness.right
+            ltk, rtk = i.tkns
             self._honored[i.root] = frozenset([(ltk, rtk)])
         self._honored = frozendict(self._honored)
 

devito/operator/operator.py

@@ -31,6 +31,8 @@
                           split, timed_pass, timed_region, contains_val)
 from devito.types import (Buffer, Grid, Evaluable, host_layer, device_layer,
                           disk_layer)
+from devito.types.dimension import Thickness
+
 
 __all__ = ['Operator']
 
@@ -640,6 +642,11 @@ def _prepare_arguments(self, autotune=None, **kwargs):
         for d in reversed(toposort):
             args.update(d._arg_values(self._dspace[d], grid, **kwargs))
 
+        # Process Thicknesses
+        for p in self.parameters:
+            if isinstance(p, Thickness):
+                args.update(p._arg_values(grid=grid, **kwargs))
+
         # Process Objects
         for o in self.objects:
             args.update(o._arg_values(grid=grid, **kwargs))