research-article

GPU-Accelerated Rectilinear Steiner Tree Generation

Authors:

Yibo LinAuthors Info & Claims

ICCAD '22: Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design

Article No.: 53, Pages 1 - 9

https://doi.org/10.1145/3508352.3549434

Published: 22 December 2022 Publication History

Abstract

Rectilinear Steiner minimum tree (RSMT) generation is a fundamental component in the VLSI design automation flow. Due to its extensive usage in circuit design iterations at early design stages like synthesis, placement, and routing, the performance of RSMT generation is critical for a reasonable design turnaround time. State-of-the-art RSMT generation algorithms, like fast look-up table estimation (FLUTE), are constrained by CPU-based parallelism with limited runtime improvements. The acceleration of RSMT on GPUs is an important yet difficult task, due to the complex and non-trivial divide-and-conquer computation patterns with recursions. In this paper, we present the first GPU-accelerated RSMT generation algorithm based on FLUTE. By designing GPU-efficient data structures and levelized decomposition, table look-up, and merging operations, we incorporate large-scale data parallelism into the generation of Steiner trees. An up to 10.47× runtime speed-up has been achieved compared with FLUTE running on 40 CPU cores, filling in a critical missing component in today's GPU-accelerated design automation framework.

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Cited By

Jiang XWang JMai JDi ZLin Y(2025)A Robust FPGA Router With Optimization of High-Fanout Nets and Intra-CLB ConnectionsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2024.344721844:3(1003-1016)Online publication date: Mar-2025
https://doi.org/10.1109/TCAD.2024.3447218
Yang LSun GDing H(2023)Towards Timing-Driven Routing: An Efficient Learning Based Geometric Approach2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)10.1109/ICCAD57390.2023.10323981(1-9)Online publication date: 28-Oct-2023
https://doi.org/10.1109/ICCAD57390.2023.10323981

Index Terms

GPU-Accelerated Rectilinear Steiner Tree Generation

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cover image ACM Conferences

ICCAD '22: Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design

October 2022

1467 pages

ISBN:9781450392174

DOI:10.1145/3508352

Conference Chair:
Tulika Mitra
National University of Singapore
,
Program Chairs:
Evangeline Young
The Chinese University of Hong Kong
,
Jinjun Xiong
University at Buffalo (UB)

Copyright © 2022 ACM.

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Published: 22 December 2022

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ICCAD '22: IEEE/ACM International Conference on Computer-Aided Design

October 30 - November 3, 2022

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Cited By

Jiang XWang JMai JDi ZLin Y(2025)A Robust FPGA Router With Optimization of High-Fanout Nets and Intra-CLB ConnectionsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2024.344721844:3(1003-1016)Online publication date: Mar-2025
https://doi.org/10.1109/TCAD.2024.3447218
Yang LSun GDing H(2023)Towards Timing-Driven Routing: An Efficient Learning Based Geometric Approach2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)10.1109/ICCAD57390.2023.10323981(1-9)Online publication date: 28-Oct-2023
https://doi.org/10.1109/ICCAD57390.2023.10323981

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