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  3. Reinforcement Learning Cuts Routing Violations in Dense Chip Layouts (NYU)

Semiconductor Engineering

Reinforcement Learning Cuts Routing Violations in Dense Chip Layouts (NYU)

Researchers at New York University published a technical paper titled “Routing Dense Layouts with History-Aware Offline Reinforcement Learning using LSTM.” Abstract Excerpt: “Detailed routing remains a dominant runtime bottleneck in physical design due to increasing complexity of design rules. Modern routers can struggle to resolve persistent violations under dense operating conditions. While recent work leverages... » read more The post Reinforcement Learning Cuts Routing Violations in Den

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19 September 2026|1 分钟阅读
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