Fast Predictive Useful Skew Methodology for Timing-Driven Placement Optimization

Abstract

Incremental timing-driven placement (TDP) is one of the most crucial steps for timing closure in a physical design. The need for high-performance incremental TDP continues to grow, but prior studies have focused on optimizing only setup timing slacks, which can be easily stuck in local optima. In this paper, we present a useful skew methodology based on a maximum mean weight cycle (MMWC) approach in the incremental TDP. The proposed useful skew methodology finds an optimal clock latency for each flip-flop, and the clock latency is implemented by moving the flip-flops and/or reassigning them to local clock buffers. With the proposed TDP method, we effectively reduce the early slack of ICCAD 2015 contest benchmarks, and achieve 124(%) and 78(%) of total quality score improvement compared to the 2015 contest winner, and early slack histogram compression (EHC) method, respectively. Moreover, with fewer iterations in the optimization, the runtime of our predictive useful skew method is an average of 7.4 times faster than an EHC method.