[Research 🤖] Chip design/floorplanning with deep reinforcement learning by Google Brain

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Following the last presentation at the ML Community Day about Chip Floorplanning with Deep Reinforcement Learning, here are some more resources:

Blog posts and research papers

• Google AI blog: Chip Design with Deep Reinforcement Learning (April 2020)

• Nature: A graph placement methodology for fast chip design (June 2021) - article link from the above Google AI blog post.

• Nature: Google AI beats humans at designing computer chips (June 2021)

• Paper (arXiv): Chip Placement with Deep Reinforcement Learning (April 2020)

• Related paper (arXiv): Placement Optimization with Deep Reinforcement Learning (March 2020)

• Related paper (arXiv): Transferable Graph Optimizers for ML Compilers (October 2020)

Videos

• Graph Representation Learning for Chip Design (MLSyS 2021)

Graph Representation Learning for Chip Design

• Solving Optimization Problems in Systems and Chip Design: Google Brain Research (March 2021)

Solving Optimization Problems in Systems and Chip Design: Google Brain Research

• Reinforcement Learning for Hardware Design - Stanford MLSys Seminar (February 2021)

Reinforcement Learning for Hardware Design feat. Anna Goldie | Stanford MLSys Seminar Episode 14

• ML for Computer Systems (NeurIPS 2019)

ML for Computer Systems