The volume of convolutional neural network (CNN) models proposed for face recognition
has been continuously growing larger to better fit the large amount of training data. When …

With the end of Dennard scaling and Moore's law, it is becoming increasingly difficult to build
hardware for emerging applications that meet power and performance targets, while …

Bio-inspired neuromorphic hardware with learning ability is highly promising to achieve
human-like intelligence, particularly in terms of high energy efficiency and strong …

The application-specific instruction set processor (ASIP) has been gradually accepted in AI,
communication, media, game and industry control. The digital signal processor (DSP) is a …

Very long instruction word (VLIW) architecture is widely used in the design of digital signal
processors (DSPs) and application-specific processors because of its hardware simplicity …

Recent neural networks (NNs) with self-attention exhibit competitiveness across different AI
domains, but the essential attention mechanism brings massive computation and memory …

High performance chip design is always a hot topic in integrated circuit (IC) field. Clock
design plays a critical role in improving chip performance and affecting power consumption …

Because of its theoretical capacity-achieving property, polar code has become the coding
scheme of the control channel in the 5G communication standard. Although its encoding …

Memory technology is one of the cornerstones of heterogeneous multi-core system
efficiency. Many memory techniques are developed to give good performance within the …

Among the physical layer baseband algorithms in macro base stations, the matrix
processing has the dominant computing cost, large data access overhead, and complicated …