Efficient scheduling methods for partitioned systolic algorithms

Various methods for mapping signal processing algorithms into systolic arrays have been developed in the past few years. In this paper, efficient scheduling techniques are developed for the partitioning problem, i.e. problems with size that do not match the array size. In particular, scheduling for the locally parallel-globally sequential (LPGS) technique and the locally sequential-globally parallel (LSGP) technique are developed. The scheduling procedure developed exploits the fact that after LPGS and LSGP partitioning, the locality constraints become modified allowing for more flexibility. The new structure allows the authors to develop a flexible scheduling order for LPGS that is useful in evaluating a trade-off between execution time and size of partitioning buffers. The benefits of the scheduling techniques are illustrated with the help of matrix multiplication and least-squares examples