5 papers
Fault-Free Analog Computing with Imperfect Hardware
Zhicheng Xu, Jiawei Liu, Sitao Huang +9
The growing demand for edge computing and AI drives research into analog in-memory computing using memristors, which overcome data movement bottlenecks by computing directly within…
Hardware-Adaptive and Superlinear-Capacity Memristor-based Associative Memory
Chengping He, Mingrui Jiang, Keyi Shan +6
Brain-inspired computing aims to mimic cognitive functions like associative memory, the ability to recall complete patterns from partial cues. Memristor technology offers promising…
Real-time raw signal genomic analysis using fully integrated memristor hardware
Peiyi He, Shengbo Wang, Ruibin Mao +6
Advances in third-generation sequencing have enabled portable and real-time genomic sequencing, but real-time data processing remains a bottleneck, hampering on-site genomic analys…
Current Opinions on Memristor-Accelerated Machine Learning Hardware
Mingrui Jiang, Yichun Xu, Zefan Li +1
The unprecedented advancement of artificial intelligence has placed immense demands on computing hardware, but traditional silicon-based semiconductor technologies are approaching…
Efficient Nonlinear Function Approximation in Analog Resistive Crossbars for Recurrent Neural Networks
Junyi Yang, Ruibin Mao, Mingrui Jiang +9
Analog In-memory Computing (IMC) has demonstrated energy-efficient and low latency implementation of convolution and fully-connected layers in deep neural networks (DNN) by using p…