Validating more loop optimizations

For more aggressive optimizations which, typically, alter the loop structure of the code, such as loop distribution and fusion, loop tiling, and loop interchanges, we present a set of which establish that the transformed code satisfies all the implied data dependencies necessary for the validity of the considered transformation.We describe the necessary extensions to the VOC-64 in order to validate these structure-modifying optimizations.In our approach, optimizations take the form of equality analyses that add equality information to a common intermediate representation.The optimizer works by repeatedly applying these analyses to infer equivalences between program fragments, thus saturating the intermediate representation with equalities.This technique has been applied to several loop optimizations, including loop interchange, loop tiling, and software pipelining and appears to be quite promising.

In Co Sy, optimal code selectors and optimization strategies are generated from descriptions that reflect the features, parallelism and timing of the architecture.

cross validation as part of the model fitting procedure.

That means that the fitting including the fitting of the hyper-parameters (this is where the inner cross validation hides) is just like any other model esitmation routine.

It is one of the possible outcomes of model validation (or verification) implying that the model we have is not fit for its purpose.

In the comment answering @davips, I was thinking of tackling the instability in the CV - i.e. But you are certainly right: if we change our model based on the findings of the outer CV, yet another round of independent testing of the changed model is necessary.

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