6 citations · 10 across the 4 of their papers we have counts for
4 papers
Quasar-ViT: Hardware-Oriented Quantization-Aware Architecture Search for Vision Transformers
Zhengang Li, Alec Lu, Yanyue Xie +9
Vision transformers (ViTs) have demonstrated their superior accuracy for computer vision tasks compared to convolutional neural networks (CNNs). However, ViT models are often compu…
HeatViT: Hardware-Efficient Adaptive Token Pruning for Vision Transformers
Peiyan Dong, Mengshu Sun, Alec Lu +8
While vision transformers (ViTs) have continuously achieved new milestones in the field of computer vision, their sophisticated network architectures with high computation and memo…
SASA: A Scalable and Automatic Stencil Acceleration Framework for Optimized Hybrid Spatial and Temporal Parallelism on HBM-based FPGAs
Xingyu Tian, Zhifan Ye, Alec Lu +3
Stencil computation is one of the fundamental computing patterns in many application domains such as scientific computing and image processing. While there are promising studies th…
Auto-ViT-Acc: An FPGA-Aware Automatic Acceleration Framework for Vision Transformer with Mixed-Scheme Quantization
Zhengang Li, Mengshu Sun, Alec Lu +9
Vision transformers (ViTs) are emerging with significantly improved accuracy in computer vision tasks. However, their complex architecture and enormous computation/storage demand i…