29 citations · 53 across the 6 of their papers we have counts for
6 papers
NAND-SPIN-Based Processing-in-MRAM Architecture for Convolutional Neural Network Acceleration
Yinglin Zhao, Jianlei Yang, Bing Li +7
The performance and efficiency of running large-scale datasets on traditional computing systems exhibit critical bottlenecks due to the existing "power wall" and "memory wall" prob…
TCIM: Triangle Counting Acceleration With Processing-In-MRAM Architecture
Xueyan Wang, Jianlei Yang, Yinglin Zhao +7
Triangle counting (TC) is a fundamental problem in graph analysis and has found numerous applications, which motivates many TC acceleration solutions in the traditional computing p…
Hardware Security in Spin-Based Computing-In-Memory: Analysis, Exploits, and Mitigation Techniques
Xueyan Wang, Jianlei Yang, Yinglin Zhao +3
Computing-in-memory (CIM) is proposed to alleviate the processor-memory data transfer bottleneck in traditional Von-Neumann architectures, and spintronics-based magnetic memory has…
Efficient Computation Reduction in Bayesian Neural Networks Through Feature Decomposition and Memorization
Xiaotao Jia, Jianlei Yang, Runze Liu +3
Bayesian method is capable of capturing real world uncertainties/incompleteness and properly addressing the over-fitting issue faced by deep neural networks. In recent years, Bayes…
SPINBIS: Spintronics based Bayesian Inference System with Stochastic Computing
Xiaotao Jia, Jianlei Yang, Pengcheng Dai +3
Bayesian inference is an effective approach for solving statistical learning problems, especially with uncertainty and incompleteness. However, Bayesian inference is a computing-in…
Spintronics based Stochastic Computing for Efficient Bayesian Inference System
Xiaotao Jia, Jianlei Yang, Zhaohao Wang +4
Bayesian inference is an effective approach for solving statistical learning problems especially with uncertainty and incompleteness. However, inference efficiencies are physically…