tree-optimization/116002 - PTA solving slow with degenerate graph

When the constraint graph consists of N nodes with only complex
constraints and no copy edges we have to be lucky to arrive at
a constraint solving order that requires the optimal number of
iterations.  What happens in the testcase is that we bottle-neck
on computing the visitation order but propagate changes only
very slowly.  Luckily the testcase complex constraints are
all copy-with-offset and those do provide a way to order
visitation.  The following adds this which reduces the iteration
count to one.

	PR tree-optimization/116002
	* tree-ssa-structalias.cc (topo_visit): Also consider
	SCALAR = SCALAR complex constraints as edges.

diff --git a/gcc/tree-ssa-structalias.cc b/gcc/tree-ssa-structalias.cc
index 330e64e65da18a7c34307a90181420c403ba2a56..65f9132a94fd46470ad64ee78aededb4205b7642 100644 (file)
--- a/gcc/tree-ssa-structalias.cc
+++ b/gcc/tree-ssa-structalias.cc
@@ -1908,6 +1908,18 @@ topo_visit (constraint_graph_t graph, vec<unsigned> &topo_order,
          topo_visit (graph, topo_order, visited, k);
       }
 
+  /* Also consider copy with offset complex constraints as implicit edges.  */
+  for (auto c : graph->complex[n])
+    {
+      /* Constraints are ordered so that SCALAR = SCALAR appear first.  */
+      if (c->lhs.type != SCALAR || c->rhs.type != SCALAR)
+       break;
+      gcc_checking_assert (c->rhs.var == n);
+      unsigned k = find (c->lhs.var);
+      if (!bitmap_bit_p (visited, k))
+       topo_visit (graph, topo_order, visited, k);
+    }
+
   topo_order.quick_push (n);
 }