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While loop restructuring based code optimization for array intensiveapplications has been successful in the past, it has several problems such asthe requirement of checking dependences (legality issues) and transformation ofall of the array references within the loop body indiscriminately (while someof the references can benefit from the transformation, others may not). As aresult, data transformations, i.e., transformations that modify memory layoutof array data instead of loop structure have been proposed. One of the problemsassociated with data transformations is the difficulty of selecting a memorylayout for an array that is acceptable to the entire program (not just to asingle loop). In this paper, we formulate the problem of determining the memorylayouts of arrays as a constraint network, and explore several methods ofsolution in a systematic way. Our experiments provide strong support in favorof employing constraint processing, and point out future research directions.

A Constraint Network Based Approach to Memory Layout Optimization