[Tiling rewrite pt1] Normalize reads and writes to common iter space (#153723)

In order to take the globally best tiling, we need to normalize all the node read and writes to a common iteration space. This first pr finds a common split among nodes in a fused scheduler node, and then normalizes reads and writes to the common split.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/153723
Approved by: https://github.com/jansel

torch/_inductor/codegen/simd.py

@@ -705,6 +705,26 @@ class SIMDKernel(Kernel[CSEVariableType], Generic[CSEVariableType]):
 
         return new_ranges, return_getters_groups
 
+    @classmethod
+    def prepare_split_iteration_lengths(
+        cls,
+        groups: Iterable[sympy.Expr],
+        lengths: Sequence[Sequence[sympy.Expr]],
+        reduction_numel: sympy.Expr = sympy.S.One,
+    ) -> Sequence[Sequence[sympy.Expr]]:
+        "Fill in the reduction numel of lengths if missing"
+        sizevars = V.graph.sizevars
+        if len(lengths[1]) == 0 and (
+            not sizevars.statically_known_equals(reduction_numel, sympy.S.One)
+            and sizevars.statically_known_equals(
+                sympy_product(groups),
+                sympy_product(lengths[0]) * reduction_numel,
+            )
+        ):
+            return (lengths[0], [reduction_numel])
+
+        return lengths
+
     @classmethod
     def is_compatible(
         cls,
@@ -712,15 +732,7 @@ class SIMDKernel(Kernel[CSEVariableType], Generic[CSEVariableType]):
         lengths: Sequence[Sequence[sympy.Expr]],
         reduction_numel: sympy.Expr = sympy.S.One,
     ) -> bool:
-        # Fill in the reduction numel, in case the node is missing it.
-        sizevars = V.graph.sizevars
-        if len(lengths[1]) == 0 and (
-            sizevars.statically_known_equals(
-                sympy_product(groups),
-                sympy_product(lengths[0]) * reduction_numel,
-            )
-        ):
-            lengths = (lengths[0], [reduction_numel])
+        lengths = cls.prepare_split_iteration_lengths(groups, lengths, reduction_numel)
 
         try:
             cls._split_iteration_ranges(groups, lengths)