HeteroExcept: A CPU-GPU Heterogeneous Algorithm to Accelerate Exception-aware Static Timing Analysis
Year: 2024
Type: conference-paper
Abstract: Static timing analysis (STA) for large-scale modern circuits requires extensive handling of false paths, multi-cycle paths, and other types of path exceptions. Despite the linear nature of timing propagation, we show that exception-aware STA is NP-hard and thus requires a long runtime to solve using conventional CPU-based methods. To overcome this runtime challenge, we propose a general CPU-GPU heterogeneous algorithm, HeteroExcept, that can handle common types of path exceptions and efficiently generate an accurate path report. Our algorithm targets runtime efficiency at the scale of thousands of exception rules and millions of circuit elements. To further improve the performance, we optimize our GPU implementation by introducing a cost-effective data exchange strategy between CPU and GPU. Experimental results demonstrate up to 6.84× and 12.93× speed-up compared to industrial timers, PrimeTime and OpenSTA.
Authors: Zizheng Guo, Zuodong Zhang, Wuxi Li, Tsung-Wei Huang, Xizhe Shi, Yufan Du, Yibo Lin, Runsheng Wang, Ru Huang
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Awards: G1169248078, G1474490597, G1953188521, FuSe-TG: Co-Design of Chiral Quantum Photonic Devices and Circuits Integrated with 2D Material Heterostructures, OAC Core: Transpass: Transpiling Parallel Task Graph Programming Models for Scientific Software, CAREER: HeteroTime: Accelerating Static Timing Analysis with Intelligent Heterogeneous Parallelism, SHF: Small: A General-purpose Parallel and Heterogeneous Task Graph Computing System for VLSI CAD, G5962490683, POSE: Phase I: Toward a Task-Parallel Programming Ecosystem for Modern Scientific Computing, G942610218
OpenAlex ID: W4409282527