iEDA: An Open-Source Intelligent Physical Implementation Toolkit and Library
Xingquan Li, Simin Tao, Zengrong Huang, Shijian Chen, Zhisheng Zeng,, Liwei Ni, Zhipeng Huang, Chunan Zhuang, Hongxi Wu, Weiguo Li1, Xueyan Zhao,, He Liu, Shuaiying Long, Wei He, Bojun Liu, Sifeng Gan, Zihao Yu, Tong Liu,, Yuchi Miao, Zhiyuan Yan, Hao Wang, Jie Zhao, Yifan Li

TL;DR
iEDA is an open-source EDA toolkit that provides a comprehensive infrastructure for physical design and analysis, demonstrated by successful chip tapeouts across various scales and process nodes.
Contribution
This work introduces a complete open-source physical design toolkit, bridging the industrial-academic gap and enabling chip design innovation.
Findings
Successfully tapeouted three chips of different scales using iEDA
iEDA covers the entire physical design flow and analysis tools
Demonstrates effectiveness across multiple process nodes
Abstract
Open-source EDA shows promising potential in unleashing EDA innovation and lowering the cost of chip design. This paper presents an open-source EDA project, iEDA, aiming for building a basic infrastructure for EDA technology evolution and closing the industrial-academic gap in the EDA area. iEDA now covers the whole flow of physical design (including Floorplan, Placement, CTS, Routing, Timing Optimization etc.), and part of the analysis tools (Static Timing Analysis and Power Analysis). To demonstrate the effectiveness of iEDA, we implement and tape out three chips of different scales (from 700k to 1.5M gates) on different process nodes (110nm and 28nm) with iEDA. iEDA is publicly available from the project home page http://ieda.oscc.cc.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsLow-power high-performance VLSI design · VLSI and FPGA Design Techniques · Parallel Computing and Optimization Techniques
