Timing and Code Size Optimization on Achieving Full Parallelism in Uniform Nested Loops

Multidimensional Retiming is one of the most important optimization techniques to improve timing parameters of nested loops. It consists in exploring the iterative and recursive structures of loops to redistribute computation nodes on cycle periods, and thus to achieve full parallelism. However, this technique introduces a large overhead in a loop generation due to the loop transformation. The provided solutions are generally characterized by an important cycle number and a great code size. It represents the most limiting factors while implementing them in embedded systems. In this paper, we present a new Multidimensional Retiming technique, called "Optimal Multidimensional Retiming" (OMDR). It reveals the timing and data dependency characteristics of nodes, to minimize the overhead. The experimental results show that the average improvement on the execution time of the nested loops by our technique is 19.31% compared to the experiments provided by an existent Multidimensional Retiming Technique. The average code size is reduced by 43.53% compared to previous experiments.