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Efficient Non-Linear Adder for Stochastic Computing with Approximate Spatial-Temporal Sorting Network
Yixuan Hu, Tengyu Zhang, Meng Li, Renjie Wei, Liangzhen Lai, Yuan Wang, Runsheng Wang, Ru Huang
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Accurate yet Efficient Stochastic Computing Neural Acceleration with High Precision Residual Fusion
Yixuan Hu, Tengyu Zhang, Renjie Wei, Meng Li, Runsheng Wang, Yuan Wang, Ru Huang
Paper
READ: Reliability-Enhanced Accelerator Dataflow Optimization using Critical Input Pattern Reduction
Zuodong Zhang, Meng Li, Yibo Lin, Runsheng Wang, Ru Huang
Paper
BiT: Robustly Binarized Multi-distilled Transformer
Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih, Meng Li, Raghuraman Krishnamoorthi, Yashar Mehdad
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Depth Shrink: Empowering Hardware-Friendly Shallow Neural Networks
Yonggan Fu, Haichuan Yang, Jiayi Yuan, Meng Li, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan Lin
Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation
Vision Transformers (ViTs) have emerged with superior performance on computer vision tasks compared to convolutional neural network …
Jiaqi Gu, Hyoukjun Kwon, Dilin Wang, Wei Ye, Meng Li, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra, David Pan
Paper
DNA: Differentiable Network-Accelerator Co-Search
Powerful yet complex deep neural networks (DNNs) have fueled a booming demand for efficient DNN solutions to bring DNN-powered …
Yongan Zhang, Yonggan Fu, Weiwen Jiang, Chaojian Li, Haoran You, Meng Li, Vikas Chandra, Yingyan Lin
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AlphaNet: Improved Training of Supernets with Alpha-Divergence
Weight-sharing neural architecture search (NAS) is an effective technique for automating efficient neural architecture design. …
Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra
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AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling
An attentive sampling strategy that improves weight-sharing neural architecture search across a broad efficiency range.
Dilin Wang, Meng Li, Chengyue Gong, Vikas Chandra
Paper
Improving efficiency in neural network accelerator using operands hamming distance optimization
Neural network accelerator is a key enabler for the on-device AI inference, for which energy efficiency is an important metric. The …
Meng Li, Yilei Li, Vikas Chandra
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