In the past decade artificial intelligence has undergone vast development thanks to deep
learning techniques. However, the large computation overhead limits the application of AI in …

In our digital era, marked by an exponential growth in computational power and memory
capacity, we are confronted with a pressing challenge: the escalating energy consumption of …

Progress in hardware and algorithms for artificial intelligence (AI) has ushered in large
machine learning models and various applications impacting our everyday lives. However …

Neuromorphic computing is an approach to efficiently solve complicated learning and
cognition problems like the human brain using electronics. To efficiently implement the …

Neuromorphic computing systems are under heavy investigation as a potential substitute for
the traditional von Neumann systems in high-speed low-power applications. Recently …

Neuromorphic computing, which aims to replicate the information processing capabilities of
the human brain, has gained significant attention as a promising paradigm for developing …

The expeditious development of information technology has led to the rise of artificial
intelligence (AI). However, conventional computing systems are prone to volatility, high …

The rapid growth of artificial intelligence demands computing hardware with higher
computing power and energy efficiency. Amid the slowdown of Moore's law scaling …

The definition of a memristor was introduced by Professor LO Chua in 1971. By generalizing
the definition of a memristor, memristive devices and systems were also proposed. Since the …

The explosion of big data applications imposes severe challenges of data processing speed
and scalability on computing system. However, the performance of the von Neumann …