A Central Challenge On The Road To AIoT Is Power-efficient Smart Chips

Modern electronic equipment is rapidly developing toward intelligence, light weight, and portability, but the challenge of intelligent big data processing and the bottleneck of von Neumann's computing architecture have become one of the key contradictions in the current electronic information field; ) The power consumption and reliability problems brought about further exacerbated the rapid deterioration of this contradiction.

In recent years, new data-centric computing architectures, such as computing-in-memory chip technology, have attracted widespread attention, especially in end-side intelligent scenarios. However, based on the consideration of many factors such as resources, delay, cost, and power consumption of end-side devices, the industry puts forward strict requirements for computing-in-memory chips. Therefore, the integration of computing-in-memory media and computing paradigms is particularly important. At the same time, device-chip-algorithm-application cross-layer collaboration is critical to the industrial application and ecological construction of memory-computing integrated chips. This article makes a brief overview of the demand, current situation, mainstream direction, application prospects and challenges of the end-side intelligent computing-in-memory chip. We have reason to believe that with the hardware support of high-energy-efficiency and low-cost intelligent computing-in-memory chips, with the maturity of 5G communication and Internet of Things (IoT) technologies, the era of Intelligent Internet of Everything (AIoT) is coming.

Since the fourth information revolution, modern electronic equipment has developed rapidly towards intelligence, light weight and portability. Especially in recent years, with the in-depth research and popularization of artificial intelligence algorithms represented by deep learning neural networks, smart electronic devices and related application scenarios have been seen everywhere, such as face recognition, voice recognition, smart home, security monitoring, unmanned driving etc. At the same time, with the maturity of 5G communication and Internet of Things (IoT) technology, it is foreseeable that the era of Intelligent Internet of Everything (AIoT) is coming.

In the future AIoT scenario, devices will be mainly divided into three categories: cloud, edge and terminal, among which edge terminal devices will show explosive growth. As we all know, the three elements of artificial intelligence are computing power, data and algorithms. The popularization of Internet and 5G communication has solved the big data problem, the rapid development of deep learning neural network has solved the algorithm problem, and the large-scale industrialization of high-performance hardware such as Nvidia GPU/Google TPU has solved the problem of cloud computing power. However, the computing power of resource-constrained edge terminal devices is still a missing link, and because of its special requirements for delay, power consumption, cost, and security, it will become the core key to large-scale industrial applications of AIoT . Therefore, on the road to AIoT, the core challenge that needs to be solved is an end-side smart chip with high energy efficiency, low cost, and long standby time.

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