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20232026
most citedLLM4EDA: Emerging Progress in Large Language Models for Electronic Design Automation

11 citations · 15 across the 11 of their papers we have counts for

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8 papers · 1 filter

cs.AR2026

How Can Reinforcement Learning Achieve Expert-level Placement?

Ruo-Tong Chen, Ke Xue, Chengrui Gao +7

Chip placement is a critical step in physical design. While reinforcement learning (RL)-based methods have recently emerged, their training primarily focuses on wirelength optimiza…

cs.AR2026

FlowPlace: Flow Matching for Chip Placement

Peng Xie, Ke Xue, Yunqi Shi +6

Chip placement plays an important role in physical design. While generative models like diffusion models offer promising learning-based solutions, current methods have the followin…

cs.AR2025

ReMaP: Macro Placement by Recursively Prototyping and Packing Tree-based Relocating

Yunqi Shi, Xi Lin, Zhiang Wang +8

This work introduces the ReMaP method, which generates expert-quality macro placements through recursively prototyping and packing tree-based relocating. We first perf…

cs.AR2025

Piano: A Multi-Constraint Pin Assignment-Aware Floorplanner

Zhexuan Xu, Kexin Zhou, Jie Wang +5

Floorplanning is a critical step in VLSI physical design, increasingly complicated by modern constraints such as fixed-outline requirements, whitespace removal, and the presence of…

cs.AR2025★ 1 cited

Open3DBench: Open-Source Benchmark for 3D-IC Backend Implementation and PPA Evaluation

Yunqi Shi, Chengrui Gao, Wanqi Ren +6

This work introduces Open3DBench, an open-source 3D-IC backend implementation benchmark built upon the OpenROAD-flow-scripts framework, enabling comprehensive evaluation of power,…

cs.AR2025★ 1 cited

Timing-Driven Global Placement by Efficient Critical Path Extraction

Yunqi Shi, Siyuan Xu, Shixiong Kai +4

Timing optimization during the global placement of integrated circuits has been a significant focus for decades, yet it remains a complex, unresolved issue. Recent analytical metho…

cs.AR2024

Benchmarking End-To-End Performance of AI-Based Chip Placement Algorithms

Zhihai Wang, Zijie Geng, Zhaojie Tu +12

The increasing complexity of modern very-large-scale integration (VLSI) design highlights the significance of Electronic Design Automation (EDA) technologies. Chip placement is a c…

cs.AR2023★ 11 cited

LLM4EDA: Emerging Progress in Large Language Models for Electronic Design Automation

Ruizhe Zhong, Xingbo Du, Shixiong Kai +7

Driven by Moore's Law, the complexity and scale of modern chip design are increasing rapidly. Electronic Design Automation (EDA) has been widely applied to address the challenges e…