Precompute the cache_key

In the /sumfact_poisson_dg_3d_unstructured_deg2_symdiff_nonquadvec_gradvec
test case this reduces the time spent in evaluation of it from >100s to 6s.

python/dune/codegen/sumfact/symbolic.py

@@ -562,6 +562,9 @@ class SumfactKernel(SumfactKernelBase, ImmutableRecord, prim.Variable):
         ImmutableRecord.__init__(self, **defaultdict)
         prim.Variable.__init__(self, "SUMFACT")
 
+        # Precompute and cache a number of keys
+        self._cached_cache_key = None
+
     #
     # The methods/fields needed to get a well-formed pymbolic node
     #
@@ -617,12 +620,15 @@ class SumfactKernel(SumfactKernelBase, ImmutableRecord, prim.Variable):
         Any two sum factorization kernels having the same cache_key
         are realized simultaneously!
         """
-        if self.buffer is None:
-            # During dry run, we return something unique to this kernel
-            return repr(self)
-        else:
-            # Later we identify parallely implemented kernels by the assigned buffer
-            return self.buffer
+        if self._cached_cache_key is None:
+            if self.buffer is None:
+                # During dry run, we return something unique to this kernel
+                self._cached_cache_key = repr(self)
+            else:
+                # Later we identify parallely implemented kernels by the assigned buffer
+                self._cached_cache_key = self.buffer
+
+        return self._cached_cache_key
 
     @property
     def inout_key(self):
@@ -865,6 +871,9 @@ class VectorizedSumfactKernel(SumfactKernelBase, ImmutableRecord, prim.Variable)
 
         prim.Variable.__init__(self, "VecSUMFAC")
 
+        # Precompute and cache a number of keys
+        self._cached_cache_key = None
+
     def __getinitargs__(self):
         return (self.kernels, self.horizontal_width, self.vertical_width, self.buffer, self.insn_dep)
 
@@ -897,7 +906,10 @@ class VectorizedSumfactKernel(SumfactKernelBase, ImmutableRecord, prim.Variable)
         Any two sum factorization kernels having the same cache_key
         are realized simulatenously!
         """
-        return (self.matrix_sequence_quadrature_permuted, self.restriction, self.stage, self.buffer)
+        if self._cached_cache_key is None:
+            self._cached_cache_key = (self.matrix_sequence_quadrature_permuted, self.restriction, self.stage, self.buffer)
+
+        return self._cached_cache_key
 
     #
     # Deduce all data fields of normal sum factorization kernels from the underlying kernels