Accelerator

Stochastic Multivariate Universal-Radix Finite-State Machine: a Theoretically and Practically Elegant Nonlinear Function Approximator
Xincheng Feng, Guodong Shen, Jianhao Hu, Meng Li, Ngai Wong
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
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
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, Meng Li, Hyoukjun Kwon, Liangzhen Lai, Tushar Krishna, Vikas Chandra, Weiwen Jiang, Yiyu Shi