电子设计自动化的强化学习:成功与机遇

Matthew E. Taylor
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引用次数: 1

摘要

强化学习是一种机器学习技术,已经应用于许多领域,包括机器人、游戏和金融。本讲座将简要介绍强化学习与编译器优化和芯片设计相关的两个用例。感兴趣的参与者还将获得关于这个令人兴奋的工具的技术或非技术级别的建议学习材料。
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Reinforcement Learning for Electronic Design Automation: Successes and Opportunities
Reinforcement learning is a machine learning technique that has been applied in many domains, including robotics, game playing, and finance. This talk will briefly introduce reinforcement learning with two use cases related to compiler optimization and chip design. Interested participants will also have materials suggested to learn a more at a technical or non-technical level about this exciting tool.
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Reinforcement Learning for Placement Optimization Session details: Session 8: Monolithic 3D and Packaging Session ISPD 2021 Wafer-Scale Physics Modeling Contest: A New Frontier for Partitioning, Placement and Routing Scalable System and Silicon Architectures to Handle the Workloads of the Post-Moore Era A Lifetime of ICs, and Cross-field Exploration: ISPD 2021 Lifetime Achievement Award Bio
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