most citedAuto-ViT-Acc: An FPGA-Aware Automatic Acceleration Framework for Vision Transformer with Mixed-Scheme Quantization

6 citations · 10 across the 4 of their papers we have counts for

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cs.AR2022★ 2 cited

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…

cs.AR2022★ 2 cited

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…