18 citations · 18 across the 12 of their papers we have counts for
7 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…
DRIFT: Harnessing Inherent Fault Tolerance for Efficient and Reliable Diffusion Model Inference
Jinqi Wen, Tong Xie, Runsheng Wang +1
Diffusion model deployment has been suffering from high energy consumption and inference latency despite its superior performance in visual generation tasks. Dynamic voltage and fr…
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…
CREATE: Cross-Layer Resilience Characterization and Optimization for Efficient yet Reliable Embodied AI Systems
Tong Xie, Yijiahao Qi, Jinqi Wen +9
Embodied Artificial Intelligence (AI) has recently attracted significant attention as it bridges AI with the physical world. Modern embodied AI systems often combine a Large Langua…
No Redundancy, No Stall: Lightweight Streaming 3D Gaussian Splatting for Real-time Rendering
Linye Wei, Jiajun Tang, Fan Fei +3
3D Gaussian Splatting (3DGS) enables high-quality rendering of 3D scenes and is getting increasing adoption in domains like autonomous driving and embodied intelligence. However, 3…
Ironman: Accelerating Oblivious Transfer Extension for Privacy-Preserving AI with Near-Memory Processing
Chenqi Lin, Kang Yang, Tianshi Xu +6
With the wide application of machine learning (ML), privacy concerns arise with user data as they may contain sensitive information. Privacy-preserving ML (PPML) based on cryptogra…