21 citations · 21 across the 11 of their papers we have counts for
6 papers · 1 filter
Aging Aware Adaptive Voltage Scaling for Reliable and Efficient AI Accelerators
Tong Xie, Zuodong Zhang, Chao Yang +3
Deep neural networks (DNNs) have showcased remarkable performance across various tasks and are widely deployed on AI accelerators fabricated in advanced technology nodes for effici…
The Quest for Reliable AI Accelerators: Cross-Layer Evaluation and Design Optimization
Meng Li, Tong Xie, Zuodong Zhang +1
As the CMOS technology pushes to the nanoscale, aging effects and process variations have become increasingly pronounced, posing significant reliability challenges for AI accelerat…
GAP-LA: GPU-Accelerated Performance-Driven Layer Assignment
Chunyuan Zhao, Zizheng Guo, Zuodong Zhang +1
Layer assignment is critical for global routing of VLSI circuits. It converts 2D routing paths into 3D routing solutions by determining the proper metal layer for each routing segm…
ReaLM: Reliable and Efficient Large Language Model Inference with Statistical Algorithm-Based Fault Tolerance
Tong Xie, Jiawang Zhao, Zishen Wan +5
The demand for efficient large language model (LLM) inference has propelled the development of dedicated accelerators. As accelerators are vulnerable to hardware faults due to agin…
The Dawn of AI-Native EDA: Opportunities and Challenges of Large Circuit Models
Lei Chen, Yiqi Chen, Zhufei Chu +36
Within the Electronic Design Automation (EDA) domain, AI-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies.…
READ: Reliability-Enhanced Accelerator Dataflow Optimization using Critical Input Pattern Reduction
Zuodong Zhang, Renjie Wei, Meng Li +3
With the rapid advancements of deep learning in recent years, hardware accelerators are continuously deployed in more and more safety-critical applications such as autonomous drivi…