Reinforcement learning for chip design

Reinforcement learning for chip design

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Episode
88 of 336
Duration
44min
Language
English
Format
Category
Non-fiction

Daniel and Chris have a fascinating discussion with Anna Goldie and Azalia Mirhoseini from Google Brain about the use of reinforcement learning for chip floor planning - or placement - in which many new designs are generated, and then evaluated, to find an optimal component layout. Anna and Azalia also describe the use of graph convolutional neural networks in their approach.

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Featuring:

• Anna Goldie – GitHub • , LinkedIn • , X • Azalia Mirhoseini – LinkedIn • , X • Chris Benson – Website • , GitHub • , LinkedIn • , X • Daniel Whitenack – Website • , GitHub • , X Show Notes:

Their research paperGoogle BrainGoogle is using AI to design chips that will accelerate AI | MIT Technology ReviewPractical AI episode #47: GANs, RL, and transfer learning oh my! Something missing or broken? PRs welcome!


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