18 citations · 40 across the 6 of their papers we have counts for
6 papers
Ferroelectric FET based Context-Switching FPGA Enabling Dynamic Reconfiguration for Adaptive Deep Learning Machines
Yixin Xu, Zijian Zhao, Yi Xiao +16
Field Programmable Gate Array (FPGA) is widely used in acceleration of deep learning applications because of its reconfigurability, flexibility, and fast time-to-market. However, c…
ALL-MASK: A Reconfigurable Logic Locking Method for Multicore Architecture with Sequential-Instruction-Oriented Key
Jianfeng Wang, Zhonghao Chen, Jiahao Zhang +9
Intellectual property (IP) piracy has become a non-negligible problem as the integrated circuit (IC) production supply chain is becoming increasingly globalized and separated that…
FAST: A Fully-Concurrent Access Technique to All SRAM Rows for Enhanced Speed and Energy Efficiency in Data-Intensive Applications
Yiming Chen, Yushen Fu, Mingyen Lee +5
Compute-in-memory (CiM) is a promising approach to improving the computing speed and energy efficiency in dataintensive applications. Beyond existing CiM techniques of bitwise logi…
Hardware Functional Obfuscation With Ferroelectric Active Interconnects
Tonggunag Yu, Yixin Xu, Shan Deng +8
Camouflaging gate techniques are typically used in hardware security to prevent reverse engineering. Layout level camouflaging by adding dummy contacts ensures some level of protec…
STAR: Sparse Transformer-based Action Recognition
Feng Shi, Chonghan Lee, Liang Qiu +6
The cognitive system for human action and behavior has evolved into a deep learning regime, and especially the advent of Graph Convolution Networks has transformed the field in rec…
Communication-efficient k-Means for Edge-based Machine Learning
Hanlin Lu, Ting He, Shiqiang Wang +5
We consider the problem of computing the k-means centers for a large high-dimensional dataset in the context of edge-based machine learning, where data sources offload machine lear…