3 citations · 10 across the 14 of their papers we have counts for
7 papers · 1 filter
CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference
Wenxuan Zeng, Meng Li, Haichuan Yang +3
Deep neural network (DNN) inference based on secure 2-party computation (2PC) can offer cryptographically-secure privacy protection but suffers from orders of magnitude latency ove…
Post-Layout Simulation Driven Analog Circuit Sizing
Xiaohan Gao, Haoyi Zhang, Siyuan Ye +6
Post-layout simulation provides accurate guidance for analog circuit design, but post-layout performance is hard to be directly optimized at early design stages. Prior work on anal…
READ: Reliability-Enhanced Accelerator Dataflow Optimization using Critical Input Pattern Reduction
Zuodong Zhang, Renjie Wei, Meng Li +3
With the rapid advancements of deep learning in recent years, hardware accelerators are continuously deployed in more and more safety-critical applications such as autonomous drivi…
Falcon: Accelerating Homomorphically Encrypted Convolutions for Efficient Private Mobile Network Inference
Tianshi Xu, Meng Li, Runsheng Wang +1
Efficient networks, e.g., MobileNetV2, EfficientNet, etc, achieves state-of-the-art (SOTA) accuracy with lightweight computation. However, existing homomorphic encryption (HE)-base…
The interface states in gate-all-around transistors (GAAFETs)
Yue-Yang Liu, Haoran Lu, Zirui Wang +5
The atomic-level structural detail and the quantum effects are becoming crucial to device performance as the emerging advanced transistors, representatively GAAFETs, are scaling do…
HybridNet: Dual-Branch Fusion of Geometrical and Topological Views for VLSI Congestion Prediction
Yuxiang Zhao, Zhuomin Chai, Yibo Lin +2
Accurate early congestion prediction can prevent unpleasant surprises at the routing stage, playing a crucial character in assisting designers to iterate faster in VLSI design cycl…