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AlphaChip is a deep reinforcement learning method for automated chip floorplanning. It was developed at Google and is now a portion of the offerings of the spinoff Ricursive. The basic ideas were introduced in a 2021 paper, which describes an approach to macro placement, a stage of chip floorplanning. It is based on reinforcement learning (RL), a machine…
Controversy, 2021 Nature paper & Background
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paper google nature placement chip macro rl evaluation designs results described approach 2021 circuit used algorithm reported learning design performance
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| AlphaChip | is a | deep reinforcement learning method for automated chip floorplanning | 0.90 | text |
| functional design changes | instance of | baseline included time spent on other tasks | 0.80 | text |
| AlphaChip | related to Author responses | Lead | 0.60 | section |
| AlphaChip | related to Author responses | Azalia Mirhoseini | 0.60 | section |
| AlphaChip | related to Author responses | Anna Goldie | 0.60 | section |
| AlphaChip | related to Author responses | Satrajit Chatterjee's | 0.60 | section |
| AlphaChip | related to Author responses | 0.60 | section | |
| AlphaChip | related to Author responses | Academics | 0.60 | section |
| AlphaChip | related to Author responses | In | 0.60 | section |
| AlphaChip | related to Author responses | Goldie | 0.60 | section |
| AlphaChip | related to Author responses | Mirhoseini | 0.60 | section |
| AlphaChip | related to Author responses | Dean | 0.60 | section |
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