Hyperplane based approach for optimizing spatial locality in loop nests

This paper presents a data layout optimization technique based on the theory of hyperplanes from linear algebra. Given a program, our framework automatically determines the optimal layouts that can be expressed by hyperplanes for each array that is referenced. We discuss the cases where data transformations are preferable to loop transformations and show that under specific conditions a loop nest can be optimized for perfect spatial locality by using data transformations. We divide the problem of optimizing data layout into two independent subproblems: (1) determining optimal layouts, and (2) determining data transformation matrices to implement optimal layouts. By postponing the determination of the transformation matrix to the last stage, our method can be adapted to compilers with different default layouts. Our results on eight programs on SGI Origin 2000 distributed-shared-memory multiprocessor show that the layout optimizations are effective in optimizing spatial locality.