Clustering for processing rate optimization

Clustering (or partitioning) is a crucial step between logic synthesis and physical design in the layout of a large scale design. A design verified at the logic synthesis level may have timing closure problems at post-layout stages due to the emergence of multiple-clock-period interconnects. Consequently, a trade-off between clock frequency and throughput may be needed to meet the design requirements. In this paper, we find that the processing rate, defined as the product of frequency and throughput, of a sequential system is upper bounded by the reciprocal of its maximum cycle ratio, which is only dependent on the clustering. We formulate the problem of processing rate optimization as seeking an optimal clustering with the minimal maximum-cycle-ratio in a general graph, and present an iterative algorithm to solve it. Since our algorithm avoids binary search and is essentially incremental, it has the potential of being combined with other optimization techniques. Experimental results validate the efficiency of our algorithm.