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About Accelerating Chip Design With Machine Learning
1) Machine learning techniques such as deep convolutional neural networks and graph-based neural networks can be applied to areas of chip design like design space exploration, power analysis, physical design, and analog design to help automate tasks. 2) The authors present a vision for an AI-assisted automated chip design workflow using techniques like neural network predictors, GPU acceleration, and reinforcement learning to further automate the VLSI design process and aid designer productivity. 3) Key ML techniques discussed that could be applied to chip design include supervised learning, unsupervised learning, deep reinforcement learning, and various neural network models to help predict outcomes and optimize the design process.
Detailed Information
| Author: | ['இரா.பவித்ர குரு'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 10 |
| Language: | English |
| Format: | |
| Price: | FREE |
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