Uniformization of affine dependence programs for parallel embedded system design

This paper is concerned with the uniformization of a system of afine recurrence equations. This transformation is used in the design (or compilation) of highly parallel embedded systems (VLSI systolic arrays, signal processing filters, etc.). In this paper, we present and implement an automatic system to achieve uniformization of systems of afine recurrence equations. We unify the results from many earlier papers, develop some theoretical extensions, and then propose effective uniformization algorithms. Our results can be used in any high level synthesis tool based on polyhedral representation of nested loop computations.

Precise analysis of array usage in scientific programs

The automatic transformation of sequential programs for efficient execution on parallel computers involves a number of analyses and restructurings of the input. Some of these analyses are based on computing array sections, a compact description of a range of array elements. Array sections describe the set of array elements that are either read or written by program statements. These sections can be compactly represented using shape descriptors such as regular sections, simple sections, or generalized convex regions. However, binary operations such as Union performed on these representations do not satisfy a straightforward closure property, e.g., if the operands to Union are convex, the result may be nonconvex. Approximations are resorted to in order to satisfy this closure property. These approximations introduce imprecision in the analyses and, furthermore, the imprecisions resulting from successive operations have a cumulative effect. Delayed merging is a technique suggested and used in some of the existing analyses to minimize the effects of approximation. However, this technique does not guarantee an exact solution in a general setting. This article presents a generalized technique to precisely compute Union which can overcome these imprecisions.