Improve codegen optimizer (pruning effectiveness)

The codegen optimizer applies various techniques to prune the search space, including the partitioning into independent problems, the restriction to interesting points, as well as cost-based and structural pruning. These techniques work very well for most use case rendering the codegen overhead negligible. However, there are still exceptions where the additional compilation overhead leads to a slowdown. One of these examples is lenet, the below codegen statistics are obtained from 1000 iterations over mnist60k.

HOP DAGs recompiled (PRED, SB): 0/1154.
HOP DAGs recompile time:        237.579 sec.
Codegen compile (DAG,CP,JC):    1176/17450/36.
Codegen enum (ALLt/p,EVALt/p):  1064354993445/16387318/11342971/11331811.
Codegen compile times (DAG,JC): 234.174/0.835 sec.
Codegen plan cache hits:        17408/17444.

Pruning reduced the number of plans from > 1 trillion to 11 million, which is still too high causing an overhead of 234s for a total execution time of 425s.