Fixups

python/dune/perftool/sumfact/vectorization.py

@@ -50,17 +50,23 @@ def attach_vectorization_info(sf):
         return _cache_vectorization_info(sf, None)
 
 
-@backend(interface="vectorization_costfunction", name="greedy")
+@backend(interface="vectorization_strategy", name="greedy")
 def greedy_costfunction(sf):
     return 1
 
 
-@backend(interface="vectorization_costfunction", name="explicit")
+@backend(interface="vectorization_strategy", name="explicit")
 def explicit_costfunction(sf):
     # Read the explicitly set values for horizontal and vertical vectorization
     width = get_vcl_type_size(np.float64)
-    horizontal = int(get_option("vectorization_horizontal", width))
-    vertical = int(get_option("vectorization_vertical", 1))
+    horizontal = get_option("vectorization_horizontal")
+    if horizontal is None:
+        horizontal = width
+    vertical = get_option("vectorization_vertical")
+    if vertical is None:
+        vertical = 1
+    horizontal = int(horizontal)
+    vertical = int(vertical)
 
     if sf.horizontal_width == horizontal and sf.vertical_width == vertical:
         return 1
@@ -71,8 +77,8 @@ def explicit_costfunction(sf):
 def strategy_cost(strategy):
     qp, strategy = strategy
     set_quadrature_points(qp)
-    func = get_backend(interface="vectorization_costfunction",
-                       name=get_option("vectorization_strategy"))
+    func = get_backend(interface="vectorization_strategy",
+                       selector=lambda: get_option("vectorization_strategy"))
     return sum(float(func(sf)) for sf in strategy.values())
 
 
@@ -80,8 +86,8 @@ def stringify_vectorization_strategy(strategy):
     result = []
     qp, strategy = strategy
 
-    result.append["Printing potential vectorization strategy:"]
-    result.append["Quadrature point tuple: {}".format(qp)]
+    result.append("Printing potential vectorization strategy:")
+    result.append("Quadrature point tuple: {}".format(qp))
 
     # Look for all realizations in the strategy and iterate over them
     cache_keys = frozenset(v.cache_key for v in strategy.values())
@@ -89,14 +95,16 @@ def stringify_vectorization_strategy(strategy):
         # Filter all the kernels that are realized by this and print
         for key in strategy:
             if strategy[key].cache_key == ck:
-                result.append["{}:".format(key)]
+                result.append("{}:".format(key))
 
         # Find one representative to print
         for val in strategy.values():
             if val.cache_key == ck:
-                result.append["    {}".format(val)]
+                result.append("    {}".format(val))
                 break
 
+    return result
+
 
 def decide_vectorization_strategy():
     """ Decide how to vectorize!
@@ -144,7 +152,7 @@ def decide_vectorization_strategy():
 
     # Register the results
     for sf in all_sumfacts:
-        _cache_vectorization_info(sf, sfdict.get(sf, no_vec(sf)))
+        _cache_vectorization_info(sf, sfdict[sf])
 
 
 def vectorization_opportunity_generator(sumfacts, width):