High performance embedded system optimization using algebraic and generalized retiming techniques

Retiming, algebraic and redundancy manipulation transformations are widely used in both the high level synthesis and the compilers fields. We present a new approach on how these powerful transformations can be applied to improve the performance of embedded systems, by optimizing their latency and throughput. A simple modification is sufficient to adapt both the Leiserson-Saxe retiming algorithm and the recently introduced ERB algorithm for the new task. We introduce a new negative retiming technique and the algorithm which coordinates this technique with both algebraic and redundancy manipulation techniques for latency optimization. The effectiveness of all discussed techniques is demonstrated on a set of “real-life” examples. Latency and throughput are improved by factors of 7.06 and 2.83 respectively, often with minimal or no additional hardware overhead