mpi: fix empty aindices halo

devito/ir/stree/algorithms.py

@@ -150,7 +150,10 @@ def preprocess(clusters, options=None, **kwargs):
     for c in clusters:
         if c.is_halo_touch:
             hs = HaloScheme.union(e.rhs.halo_scheme for e in c.exprs)
-            queue.append(c.rebuild(halo_scheme=hs))
+            if hs.distributed_aindices:
+                queue.append(c.rebuild(halo_scheme=hs))
+            else:
+                processed.append(c.rebuild(exprs=None, halo_scheme=hs))
         elif c.is_critical_region and c.syncs:
             processed.append(c.rebuild(exprs=None, guards=c.guards, syncs=c.syncs))
         elif c.is_wild:
@@ -165,7 +168,7 @@ def preprocess(clusters, options=None, **kwargs):
 
                 # Skip if the halo exchange would end up outside
                 # its iteration space
-                if h_indices and not h_indices & dims:
+                if h_indices and dims and not h_indices & dims:
                     continue
 
                 diff = dims - distributed_aindices

devito/mpi/distributed.py

@@ -17,6 +17,8 @@
 from devito.types.utils import DimensionTuple
 
 
+__all__ = ['CustomTopology']
+
 # Do not prematurely initialize MPI
 # This allows launching a Devito program from within another Python program
 # that has *already* initialized MPI

tests/test_mpi.py

@@ -6,7 +6,8 @@
 from devito import (Grid, Constant, Function, TimeFunction, SparseFunction,
                     SparseTimeFunction, Dimension, ConditionalDimension, SubDimension,
                     SubDomain, Eq, Ne, Inc, NODE, Operator, norm, inner, configuration,
-                    switchconfig, generic_derivative, PrecomputedSparseFunction)
+                    switchconfig, generic_derivative, PrecomputedSparseFunction,
+                    DefaultDimension)
 from devito.arch.compiler import OneapiCompiler
 from devito.data import LEFT, RIGHT
 from devito.ir.iet import (Call, Conditional, Iteration, FindNodes, FindSymbols,
@@ -600,6 +601,32 @@ def test_precomputed_sparse(self, r):
         Operator(sf1.interpolate(u))()
         assert np.all(sf1.data == 4)
 
+    @pytest.mark.parallel(mode=4)
+    def test_no_grid_dim_slow(self):
+        shape = (12, 13, 14)
+        nfreq = 5
+        nrec = 2
+
+        grid = Grid(shape=shape)
+        f = DefaultDimension(name="f", default_value=nfreq)
+
+        u = Function(name="u", grid=grid, dimensions=(*grid.dimensions, f),
+                     shape=(*shape, nfreq), space_order=2)
+        u.data.fill(1)
+
+        class CoordSlowSparseFunction(SparseFunction):
+            _sparse_position = 0
+
+        r = Dimension(name="r")
+        s = CoordSlowSparseFunction(name="s", grid=grid, dimensions=(r, f),
+                                    shape=(nrec, nfreq), npoint=nrec)
+
+        rec_eq = s.interpolate(expr=u)
+
+        op = Operator(rec_eq)
+        op.apply()
+        assert np.all(s.data == 1)
+
 
 class TestOperatorSimple(object):