20 citations · 22 across the 4 of their papers we have counts for
4 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…
Triangle Counting Accelerations: From Algorithm to In-Memory Computing Architecture
Xueyan Wang, Jianlei Yang, Yinglin Zhao +5
Triangles are the basic substructure of networks and triangle counting (TC) has been a fundamental graph computing problem in numerous fields such as social network analysis. Never…
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…