Efficient timing propagation with simultaneous structural and pipeline parallelisms
Cheng-Hsiang Chiu, Tsung‐Wei Huang
Abstract
Graph-based timing propagation (GBP) is an essential component for all static timing analysis (STA) algorithms. To speed up GBP, the state-of-the-art timer leverages the task graph model to explore structural parallelism in an STA graph. However, many designs exhibit linear segments that cause the parallelism to serialize, degrading the performance significantly. To overcome this problem, we introduce an efficient GBP framework by exploring both structural and pipeline parallelisms in an STA task graph. Our framework identifies linear segments and parallelizes their propagation tasks using pipeline in an STA task graph. We have shown up to 25% performance improvement over the state-of-the-art task graph-based timer.