Warp-STAR: High-performance, Differentiable GPU-Accelerated Static Timing Analysis through Warp-oriented Parallel Orchestration

TL;DR

Warp-STAR is a GPU-accelerated static timing analysis engine that uses warp-level orchestration to eliminate load imbalance, achieving significant speedups in EDA workflows.

Contribution

It introduces warp-oriented parallel orchestration to improve GPU-based static timing analysis efficiency, surpassing previous state-of-the-art methods.

Findings

2.4X speedup over previous GPU-based STA

1.7X speedup in global placement framework

Effective differentiable gradient analysis with minimal overhead

Abstract

Static timing analysis (STA) is crucial for Electronic Design Automation (EDA) flows but remains a computational bottleneck. While existing GPU-based STA engines are faster than CPU, they suffer from inefficiencies, particularly intra-warp load imbalance caused by irregular circuit graphs. This paper introduces Warp-STAR, a novel GPU-accelerated STA engine that eliminates this imbalance by orchestrating parallel computations at the warp level. This approach achieves a 2.4X speedup over previous state-of-the-art (SoTA) GPU-based STA. When integrated into a timing-driven global placement framework, Warp-STAR delivers a 1.7X speedup over SoTA frameworks. The method also proves effective for differentiable gradient analysis with minimal overhead.