11 citations · 15 across the 11 of their papers we have counts for
Showing 2024Show all
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cs.LG2024★ 1 cited
Reinforcement Learning Policy as Macro Regulator Rather than Macro Placer
Ke Xue, Ruo-Tong Chen, Xi Lin +4
In modern chip design, placement aims at placing millions of circuit modules, which is an essential step that significantly influences power, performance, and area (PPA) metrics. R…
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.LG2024★ 1 cited
Escaping Local Optima in Global Placement
Ke Xue, Xi Lin, Yunqi Shi +3
Placement is crucial in the physical design, as it greatly affects power, performance, and area metrics. Recent advancements in analytical methods, such as DREAMPlace, have demonst…