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Rongjian Liang
NVIDIA
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Machine Learning for EDA
EDA for Machine Learning
Latest
ReLS: Retrieval Is Efficient Knowledge Transfer For Logic Synthesis
Learning to Compare Hardware Designs for High-Level Synthesis
OpenROAD and CircuitOps: Infrastructure for ML EDA Research and Education
DiMO-Sparse: Differentiable Modeling and Optimization of Sparse CNN Dataflow and Hardware Architecture
GPU/ML-Enhanced Large Scale Global Routing Contest
MedPart: A Multi-Level Evolutionary Differentiable Hypergraph Partitioner
CircuitOps: An ML Infrastructure Enabling Generative AI for VLSI Circuit Optimization
Late Breaking Results: Test Selection For RTL Coverage By Unsupervised Learning From Fast Functional Simulation
BufFormer: A Generative ML Framework for Scalable Buffering
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