21 citations · 21 across the 11 of their papers we have counts for
11 papers
MacroAgent: Regularity-Aware Macro Legalization with LLM-Agent-Designed Contour Algorithms
Jiaxi Jiang, Xufeng Yao, Yuxuan Zhao +5
Macros constitute a large part of the core area in modern very large-scale integration (VLSI) designs. Moreover, macro positions have a significant impact on the final quality of r…
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…
HeteroSTA: A CPU-GPU Heterogeneous Static Timing Analysis Engine with Holistic Industrial Design Support
Zizheng Guo, Haichuan Liu, Xizhe Shi +5
We introduce in this paper, HeteroSTA, the first CPU-GPU heterogeneous timing analysis engine that efficiently supports: (1) a set of delay calculation models providing versatile a…
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…
An Energy-Efficient Mixed-Signal Parallel Multiply-Accumulate (MAC) Engine Based on Stochastic Computing
Xinyue Zhang, Jiahao Song, Yuan Wang +4
Convolutional neural networks (CNN) have achieved excellent performance on various tasks, but deploying CNN to edge is constrained by the high energy consumption of convolution ope…
Memory System Designed for Multiply-Accumulate (MAC) Engine Based on Stochastic Computing
Xinyue Zhang, Yuan Wang, Yawen Zhang +5
Convolutional neural network (CNN) achieves excellent performance on fascinating tasks such as image recognition and natural language processing at the cost of high power consumpti…
A Parallel Bitstream Generator for Stochastic Computing
Yawen Zhang, Runsheng Wang, Xinyue Zhang +5
Stochastic computing (SC) presents high error tolerance and low hardware cost, and has great potential in applications such as neural networks and image processing. However, the bi…