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20232026
most citedAdapMoE: Adaptive Sensitivity-based Expert Gating and Management for Efficient MoE Inference

18 citations · 21 across the 21 of their papers we have counts for

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7 papers · 1 filter

cs.AR2026

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…

cs.AR2026

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…

cs.AR2026

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…

cs.AR2025

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…

cs.AR2025

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…

cs.AR2024

Efficient yet Accurate End-to-End SC Accelerator Design

Meng Li, Yixuan Hu, Tengyu Zhang +4

Providing end-to-end stochastic computing (SC) neural network acceleration for state-of-the-art (SOTA) models has become an increasingly challenging task, requiring the pursuit of…

cs.AR2023

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…