AI Optimizes Final Chip Design

In this AI Research Roundup episode, Alex discusses the paper:
'LaMPlace: Learning to Optimize Cross-Stage Metrics in Macro Placement'
LaMPlace addresses a critical gap in AI-driven chip design: optimizing for final performance metrics (like timing) instead of just intermediate ones. This novel method learns to predict these crucial cross-stage metrics, using this insight to guide component placement for significantly improved chip quality.
Paper URL: openreview.net/forum?id=YLIsIzC74j

#AI #MachineLearning #DeepLearning #ChipDesign #MacroPlacement #VLSI #AIoptimization
Authors: Zijie Geng, Jie Wang, Ziyan Liu, Siyuan Xu, Zhentao Tang, Shixiong Kai, Mingxuan Yuan, Jianye HAO, Feng Wu