Efficient AI

Omni-sparsity DNN: Fast Sparsity Optimization for On-Device Streaming E2E ASR via Supernet
From wearables to powerful smart devices, modern automatic speech recognition (ASR) models run on a variety of edge devices with …
Haichuan Yang, Yuan Shangguan, Dilin Wang, 李萌, Pierce Chuang, Xiaohui Zhang, Ganesh Venkatesh, Ozlem Kalinli, Vikas Chandra
论文
SplitNets: Designing Neural Architectures for Efficient Distributed Computing on Head-Mounted Systems
We design deep neural networks (DNNs) and corresponding networks’ splittings to distribute DNNs’ workload to camera sensors …
Xin Dong, Ziyun Li, 李萌, Zhongnan Qu, Barbara De Salvo, Chiao Liu, Hsiang-Tsung Kung
论文
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training
Designing accurate and efficient vision transformers (ViTs) is a highly important but challenging task. Supernet-based one-shot neural …
Chengyue Gong, Dilin Wang, 李萌, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Qiang Liu, Vikas Chandra
论文
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, 李萌, Vikas Chandra, Yingyan Lin
论文
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, 李萌, Qiang Liu, Vikas Chandra
论文
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, 李萌, Chengyue Gong, Vikas Chandra
论文
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 …
李萌, Yilei Li, Vikas Chandra
论文
Co-exploration of neural architectures and heterogeneous asic accelerator designs targeting multiple tasks
Neural architecture search (NAS) has shown great promise in designing state-of-the-art (SOTA) models that are both accurate and …
Lei Yang, Zheyu Yan, 李萌, Hyoukjun Kwon, Liangzhen Lai, Tushar Krishna, Vikas Chandra, Weiwen Jiang, Yiyu Shi
论文