In traditional von Neumann computing architectures, the essential transfer of data between
the processor and memory hierarchies limits the computational efficiency of next-generation …

An artificial intelligence (AI) processor is a promising solution for energy-efficient data
processing, including health monitoring and image/voice recognition. However, data …

Convolution neural networks (CNNs) have demonstrated superior capability in computer
vision, speech recognition, autonomous driving, and so forth, which are opening up an …

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 …

CMOS compatible spin-transfer-torque magnetic random access memory (STT-MRAM) has
demonstrated promising developments as the next-generation embedded non-volatile …

The emergence of non-volatile memories (NVM) such as resistive-oxide random access
memory (RRAM), magnetoresistive random access memory (MRAM), and phase change …

With the rapid development of electronic measurement technology, people have put forward
higher requirements for the diversity of oscilloscope functions and abundant peripheral …

Although significant breakthrough has been made in deep neural networks (DNNs), which
show impressive potential as a general solution to the field of artificial intelligence (AI), DNN …

This focus paper provides an overview on the emerging area of in-memory neural vision
chips for building intelligent cameras. The generalization abilities of neural networks and …

Logic-in-memory architecture based on spintronic memories shows fascinating prospects in
neural networks (NNs) for its high energy efficiency and good endurance. In this work, we …