diff --git a/python/dune/perftool/sumfact/geometry.py b/python/dune/perftool/sumfact/geometry.py
index ffea761f515bd776fcd18ca0328274f00a8efec2..c8ff6c38d9b906e126f2571d065b2cea6c852a38 100644
--- a/python/dune/perftool/sumfact/geometry.py
+++ b/python/dune/perftool/sumfact/geometry.py
@@ -45,13 +45,15 @@ class GeoCornersInput(SumfactKernelInputBase, ImmutableRecord):
         # NB: We need to realize this as a C instruction, because the corner
         #     method does return a non-scalar, which does not fit into the current
         #     loopy philosophy for function calls. This problem will be solved once
-        #     #11 is resolved.
-        code = "{}[{}] = {}.corner({})[{}];".format(name,
-                                                    ciname,
-                                                    geo,
-                                                    ciname,
-                                                    self.dir,
-                                                    )
+        #     #11 is resolved. Admittedly, the code looks *really* ugly until that happens.
+        code = "{}[{}*{}+{}] = {}.corner({})[{}];".format(name,
+                                                          sf.vector_width,
+                                                          ciname,
+                                                          index,
+                                                          geo,
+                                                          ciname,
+                                                          self.dir,
+                                                          )
 
         instruction(code=code,
                     within_inames=frozenset({ciname}),
diff --git a/python/dune/perftool/sumfact/symbolic.py b/python/dune/perftool/sumfact/symbolic.py
index 90818e301475406ec4a85bb8a7e0f4a76434d4d5..a8a42ed170ea97eead8741183d4145f0d5b7ba3e 100644
--- a/python/dune/perftool/sumfact/symbolic.py
+++ b/python/dune/perftool/sumfact/symbolic.py
@@ -355,15 +355,6 @@ class VectorizedSumfactKernel(SumfactKernelBase, ImmutableRecord, prim.Variable)
         """
         return (self.matrix_sequence, self.restriction, self.stage, self.buffer)
 
-    @property
-    def input_key(self):
-        """ A cache key for the input coefficients
-        Any two sum factorization kernels having the same input_key
-        work on the same input coefficient (and are suitable for simultaneous
-        treatment because of that)
-        """
-        return (self.restriction, self.stage, self.coeff_func, self.coeff_func_index, self.element, self.component, self.accumvar)
-
     #
     # Deduce all data fields of normal sum factorization kernels from the underlying kernels
     #
@@ -419,7 +410,7 @@ class VectorizedSumfactKernel(SumfactKernelBase, ImmutableRecord, prim.Variable)
 
     @property
     def cache_key(self):
-        return tuple(k.cache_key for k in self.kernels)
+        return (tuple(k.cache_key for k in self.kernels), self.buffer)
 
     @property
     def input_key(self):
diff --git a/python/dune/perftool/sumfact/tabulation.py b/python/dune/perftool/sumfact/tabulation.py
index 90271e6552a0cca72a8b8df17178d8e48d4c4bca..6b04195775a6814acf6c9edb9e6de4bbb1dcd46e 100644
--- a/python/dune/perftool/sumfact/tabulation.py
+++ b/python/dune/perftool/sumfact/tabulation.py
@@ -173,8 +173,8 @@ class BasisTabulationMatrixArray(BasisTabulationMatrixBase):
         name = "ThetaLarge{}{}_{}_qp{}_dof{}".format("face{}_".format(self.face) if self.face is not None else "",
                                                      "T" if self.transpose else "",
                                                      "_".join(abbrevs),
-                                                     quadrature_points_per_direction(),
-                                                     basis_functions_per_direction(),
+                                                     self.tabs[0].quadrature_size,
+                                                     self.tabs[0].basis_size,
                                                      )
         for i, tab in enumerate(self.tabs):
             define_theta(name, tab, additional_indices=(i,), width=self.width)