1 citations · 1 across the 6 of their papers we have counts for
6 papers
FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design
Renjie Wei, Songqiang Xu, Qingyu Guo +1
Visual autoregressive (VAR) modeling has marked a paradigm shift in image generation from next-token prediction to next-scale prediction. VAR predicts a set of tokens at each step…
LightMamba: Efficient Mamba Acceleration on FPGA with Quantization and Hardware Co-design
Renjie Wei, Songqiang Xu, Linfeng Zhong +5
State space models (SSMs) like Mamba have recently attracted much attention. Compared to Transformer-based large language models (LLMs), Mamba achieves linear computation complexit…
A Novel Energy-Efficient Salicide-Enhanced Tunnel Device Technology Based on 300mm Foundry Platform Towards AIoT Applications
Kaifeng Wang, Qianqian Huang, Yongqin Wu +16
This work demonstrates a novel energy-efficient tunnel FET (TFET)-CMOS hybrid foundry platform for ultralow-power AIoT applications. By utilizing the proposed monolithic integratio…
ASCEND: Accurate yet Efficient End-to-End Stochastic Computing Acceleration of Vision Transformer
Tong Xie, Yixuan Hu, Renjie Wei +4
Stochastic computing (SC) has emerged as a promising computing paradigm for neural acceleration. However, how to accelerate the state-of-the-art Vision Transformer (ViT) with SC re…
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…
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…