activity
20172022
most citedPatDNN: Achieving Real-Time DNN Execution on Mobile Devices with Pattern-based Weight Pruning

211 citations · 477 across the 15 of their papers we have counts for

collaborators

22 papers

quant-ph20222 cited

Hybrid Gate-Pulse Model for Variational Quantum Algorithms

Zhiding Liang, Zhixin Song, Jinglei Cheng +8

Current quantum programs are mostly synthesized and compiled on the gate-level, where quantum circuits are composed of quantum gates. The gate-level workflow, however, introduces s…

quant-ph20227 cited

TopGen: Topology-Aware Bottom-Up Generator for Variational Quantum Circuits

Jinglei Cheng, Hanrui Wang, Zhiding Liang +3

Variational Quantum Algorithms (VQA) are promising to demonstrate quantum advantages on near-term devices. Designing ansatz, a variational circuit with parameterized gates, is of p…

cs.LG2021

GRIM: A General, Real-Time Deep Learning Inference Framework for Mobile Devices based on Fine-Grained Structured Weight Sparsity

Wei Niu, Zhengang Li, Xiaolong Ma +6

It is appealing but challenging to achieve real-time deep neural network (DNN) inference on mobile devices because even the powerful modern mobile devices are considered as ``resou…

cs.AR20219 cited

FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator

Geng Yuan, Payman Behnam, Zhengang Li +8

Recent works demonstrated the promise of using resistive random access memory (ReRAM) as an emerging technology to perform inherently parallel analog domain in-situ matrix-vector m…

cs.AR2021

HASCO: Towards Agile HArdware and Software CO-design for Tensor Computation

Qingcheng Xiao, Size Zheng, Bingzhe Wu +3

Tensor computations overwhelm traditional general-purpose computing devices due to the large amounts of data and operations of the computations. They call for a holistic solution c…

cs.LG20207 cited

Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework

Sung-En Chang, Yanyu Li, Mengshu Sun +5

Deep Neural Networks (DNNs) have achieved extraordinary performance in various application domains. To support diverse DNN models, efficient implementations of DNN inference on edg…