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Following the last presentation 1 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:  Google AI Blog: Chip Design with Deep Reinforcement Learning 2 (April 2020)


Nature: A graph placement methodology for fast chip design 1 (June 2021) - article link from the above Google AI blog post.


Nature: Google AI beats humans at designing computer chips 1 (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)


  
      

      SlidesLive
  

  
    

Graph Representation Learning for Chip Design 1



  

  
    
    
  

  



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)


  
      

      SlidesLive
  

  
    

ML for Computer Systems 1