> So a practical implementation needs good heuristics for value-ordering If I understand correctly, this would require some correlation between disparate forms

> So a practical implementation needs good heuristics for value-ordering If I understand correctly, this would require some correlation between disparate forms of optimization. I would fear that the each optimization would alter/rewrite insns significantly enough that there may not be enough correlation to build those search shortcuts. Too many guess-and-check-cost across all permutations might still be expensive. Along the same lines of determining which combination of optimizations yields the best overall, I wonder if one could train a NN to do it. Maybe there's some work in the area, I don't keep up with research. But in general I would imagine that with a large enough trained set, the NN could say a spill in case X on arch Y is likely better than a re-eval. But then you get into non-determinism which scares devs. Just a thought.