Applicable to arbitrary sequences and nests of loops, affine partitioning is a program transformation framework that unifies many previously proposed loop transformations, including unimodular transforms, fusion, fission, reindexing, scaling and statement reordering. Algorithms based on affine partitioning have been shown to be effective for parallelization and communication minimization. This paper presents algorithms that improve data locality using affine partitioning.

An affine partitioning framework unifies many useful program transforms such as unimodular transformations (interchange, reversal, skewing), loop fusion, fission, scaling, reindexing, and statement reordering. This paper presents an algorithm, based on this unified framework, that maximizes parallelism while minimizing communication in programs with arbitrary loop nestings and affine data accesses. Our algorithm can find the optimal affine partition that maximizes the degree of parallelism with the minimum degree of synchronizations. In addition, it uses a greedy algorithm to minimize communication between loops heuristically by aligning the computation partitions for different loops, trading off excess degrees of parallelism, and choosing pipelined parallelism over doall parallelism if it can significantly reduce the communication. The algorithm is optimal in maximizing the degrees of parallelism that require (1) no communication, (2) near-neighbor communication and a constant number ...

This paper presents an algorithm to find the optimal affine partitions that maximize the degree of parallelism and minimize the degree of synchronization in programs with arbitrary loop nestings and affine data accesses. The problem is formulated without the use of imprecise data dependence abstractions such as data dependence vectors. The algorithm presented subsumes previously proposed loop transformation algorithms that are based on unimodular transformations, loop distribution, fusion, scaling, reindexing, and statement reordering.

This paper presents the first algorithm to find the optimal affine transform that maximizes the degree of parallelism while minimizing the degree of synchronization in a program with arbitrary loop nestings and affine data accesses. The problem is formulated without the use of imprecise data dependence abstractions such as data dependence vectors. The algorithm presented subsumes previously proposed program transformation algorithms that are based on unimodular transformations, loop fusion, fission, scaling, reindexing and/or statement reordering.