most citedA Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining

50 citations · 54 across the 5 of their papers we have counts for

collaborators

5 papers

quant-ph20231 cited

VENUS: A Geometrical Representation for Quantum State Visualization

Shaolun Ruan, Ribo Yuan, Qiang Guan +6

Visualizations have played a crucial role in helping quantum computing users explore quantum states in various quantum computing applications. Among them, Bloch Sphere is the widel…

quant-ph2023

Battle Against Fluctuating Quantum Noise: Compression-Aided Framework to Enable Robust Quantum Neural Network

Zhirui Hu, Youzuo Lin, Qiang Guan +1

Recently, we have been witnessing the scale-up of superconducting quantum computers; however, the noise of quantum bits (qubits) is still an obstacle for real-world applications to…

cs.LG202250 cited

A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining

Hongwu Peng, Shaoyi Huang, Shiyang Chen +8

Transformers are considered one of the most important deep learning models since 2018, in part because it establishes state-of-the-art (SOTA) records and could potentially replace…

quant-ph20223 cited

VACSEN: A Visualization Approach for Noise Awareness in Quantum Computing

Shaolun Ruan, Yong Wang, Weiwen Jiang +2

Quantum computing has attracted considerable public attention due to its exponential speedup over classical computing. Despite its advantages, today's quantum computers intrinsical…

quant-ph2022

Quantum Neural Network Compression

Zhirui Hu, Peiyan Dong, Zhepeng Wang +3

Model compression, such as pruning and quantization, has been widely applied to optimize neural networks on resource-limited classical devices. Recently, there are growing interest…