activity
20192022
most citedQGAN: Quantized Generative Adversarial Networks

21 citations · 38 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2022★ 1 cited

PMUSpill: The Counters in Performance Monitor Unit that Leak SGX-Protected Secrets

Pengfei Qiu, Yongqiang Lyu, Haixia Wang +6

Performance Monitor Unit (PMU) is a significant hardware module on the current processors, which counts the events launched by processor into a set of PMU counters. Ideally, the ev…

cs.CR2021★ 3 cited

Lightning: Striking the Secure Isolation on GPU Clouds with Transient Hardware Faults

Rihui Sun, Pefei Qiu, Yongqiang Lyu +3

GPU clouds have become a popular computing platform because of the cost of owning and maintaining high-performance computing clusters. Many cloud architectures have also been propo…

cs.DC2021★ 11 cited

DynaComm: Accelerating Distributed CNN Training between Edges and Clouds through Dynamic Communication Scheduling

Shangming Cai, Dongsheng Wang, Haixia Wang +4

To reduce uploading bandwidth and address privacy concerns, deep learning at the network edge has been an emerging topic. Typically, edge devices collaboratively train a shared mod…

cs.CR2019★ 2 cited

LEAP: A Lightweight Encryption and Authentication Protocol for In-Vehicle Communications

Zhaojun Lu, Qian Wang, Xi Chen +3

The Controller Area Network (CAN) is considered as the de-facto standard for the in-vehicle communications due to its real-time performance and high reliability. Unfortunately, the…

cs.NE2019★ 21 cited

QGAN: Quantized Generative Adversarial Networks

Peiqi Wang, Dongsheng Wang, Yu Ji +5

The intensive computation and memory requirements of generative adversarial neural networks (GANs) hinder its real-world deployment on edge devices such as smartphones. Despite the…