compiler: Catch redundant IndexDerivatives early on

devito/passes/clusters/cse.py

@@ -10,7 +10,7 @@
 from devito.symbolics import estimate_cost, q_leaf
 from devito.symbolics.manipulation import _uxreplace
 from devito.tools import as_list
-from devito.types import Eq, Temp
+from devito.types import Eq, Symbol, Temp
 
 __all__ = ['cse']
 
@@ -169,15 +169,25 @@ def _(exprs):
     return mapper
 
 
-@count.register(IndexDerivative)
 @count.register(Indexed)
+@count.register(Symbol)
 def _(expr):
     """
     Handler for objects preventing CSE to propagate through their arguments.
     """
     return Counter()
 
 
+@count.register(IndexDerivative)
+def _(expr):
+    """
+    Handler for symbol-binding objects. There can be many of them and therefore
+    they should be detected as common subexpressions, but it's either pointless
+    or forbidden to look inside them.
+    """
+    return Counter([expr])
+
+
 @count.register(Add)
 @count.register(Mul)
 @count.register(Pow)

devito/passes/clusters/derivatives.py

@@ -19,6 +19,10 @@ def lower_index_derivatives(clusters, mode=None, **kwargs):
     if mode != 'noop':
         clusters = fuse(clusters, toposort='maximal')
 
+    # At this point we can detect redundancies induced by inner derivatives that
+    # previously were just not detectable via e.g. plain CSE. For example, if
+    # there were two IndexDerivatives such as `(p.dx + m.dx).dx` and `m.dx.dx`
+    # then it's only after `_lower_index_derivatives` that they're detectable!
     clusters = CDE(mapper).process(clusters)
 
     return clusters

tests/test_unexpansion.py

@@ -5,6 +5,7 @@
 from devito import (Buffer, Eq, Function, TimeFunction, Grid, Operator,
                     Substitutions, Coefficient, cos, sin)
 from devito.arch.compiler import OneapiCompiler
+from devito.ir import Expression, FindNodes, FindSymbols
 from devito.parameters import switchconfig, configuration
 from devito.types import Symbol
 
@@ -300,6 +301,30 @@ def test_transpose(self):
         op1.apply(time_M=10, u=u1)
         assert np.allclose(u.data, u1.data, rtol=10e-6)
 
+    def test_redundant_derivatives(self):
+        grid = Grid(shape=(10, 10, 10))
+
+        f = Function(name='f', grid=grid)
+        g = Function(name='g', grid=grid)
+        h = Function(name='h', grid=grid)
+        u = TimeFunction(name='u', grid=grid, space_order=4)
+
+        # It's the same `u.dx.dy` appearing multiple times, and the cost models
+        # must be smart enough to detect that!
+        eq = Eq(u.forward, (f*u.dx.dy + g*u.dx.dy + h*u.dx.dy +
+                            (f*g)*u.dx.dy + (f*h)*u.dx.dy + (g*h)*u.dx.dy))
+
+        op = Operator(eq, opt=('advanced', {'expand': False,
+                                            'blocklevels': 0}))
+
+        # Check generated code
+        assert len(get_arrays(op)) == 0
+        assert op._profiler._sections['section0'].sops == 74
+        exprs = FindNodes(Expression).visit(op)
+        assert len(exprs) == 6
+        temps = [i for i in FindSymbols().visit(exprs) if isinstance(i, Symbol)]
+        assert len(temps) == 3
+
 
 class Test2Pass(object):
 
@@ -312,14 +337,14 @@ def test_v0(self):
         v1 = TimeFunction(name='v', grid=grid, space_order=8)
 
         eqns = [Eq(u.forward, (u.dx.dy + v*u + 1.)),
-                Eq(v.forward, (v + u.dx.dy + 1.))]
+                Eq(v.forward, (v + u.dx.dz + 1.))]
 
         op0 = Operator(eqns)
         op1 = Operator(eqns, opt=('advanced', {'expand': False,
                                                'openmp': True}))
 
         # Check generated code
-        assert op1._profiler._sections['section0'].sops == 41
+        assert op1._profiler._sections['section0'].sops == 59
         assert_structure(op1, ['t',
                                't,x0_blk0,y0_blk0,x,y,z',
                                't,x0_blk0,y0_blk0,x,y,z,i0',