Recently, the Future Chip Innovation Research Institute of Xiong’an New Area was officially established in Hebei, China.

According to the official Wechat account of “Xiong’an New Area,” the Future Chip Innovation Research Institute of Xiong’an New Area was jointly founded by the RISC-V Working Committee of the China Electronics Standardization Association, Chipup, ESWIN, and Stream Computing as the initial sponsors.

The research institute will engage in technical research and development, product testing, standard formulation, evaluation, application demonstration, and collaboration based on the RISC-V open instruction set, promoting the high-quality development of the RISC-V industry in Xiong’an New Area.

RISC-V is an open instruction set architecture (ISA) based on the principles of Reduced Instruction Set Computing (RISC). Currently, open source has become a new model for global collaborative innovation. As an advanced and easily-customizable architecture, the open-source RISC-V is still in the early stage of development in terms of ecosystem.

At present, RISC-V has not only become the preferred CPU architecture in many fields in China, including IoT, industrial, medical, intelligent connected vehicles, general computing, and communication computing, but also injecting strong momentum into technological innovation and industrial transformation in the global chip industry. It is expected to gain a foothold in the CPU field and compete with x86 and ARM.

Data shows that in 2022, 10 billion processors based on the RISC-V architecture were shipped, a scale that took x86 and ARM 30 years to achieve. The industry expects that by 2025, the number of RISC-V cores will increase to 80 billion. With the advent of the artificial intelligence (AI) era, RISC-V is also expected to embrace new development opportunities.

Currently, the overall AI chip market is still dominated by GPU (Like NVIDIA, AMD), followed by Arm. TrendForce pointed out that, RISC-V has made some investment in data center in recent years, and with efforts from NVIDIA and CSPs, RISC-V is expected to become another niche market, possibly targeting the open-source AI market (Like Meta) or other niche applications.

(Photo credit: RISC-V Working Committee)

On May 16, Japanese foundry startup Rapidus announced the signing of a Memorandum of Understanding (MoU) with American RISC-V architecture chip design company, Esperanto. The two sides will collaborate on the research and development of AI semiconductors for data centers, aiming to jointly develop low-power AI chips.

Currently, according to a report from DRAMeXchange, despite the gradual ease of GPU shortage, power supply has become another bottleneck in the course of the AI development.

Industry sources cited in the report have pointed out that CPU and GPU have played a critical role in fostering the prosperity of the AI market. However, the increasing power consumption of the latest chips is causing a recent crisis. For instance, it is expected that by 2027, the energy consumed by generative AI processing will account for nearly 80% of the total electricity consumption of data centers in the United States.

Data center is a major engine to drive the growth of electricity demand. With the advent of the AI era, represented by generative AI, the power required for high-performance computing chips continuously increases, which in turn raises the electricity consumption of data centers.

Esperanto has been committed to designing large-scale parallel, high-performance, and energy-efficient computing solutions. Previously, it launched the ET-SOC-1-based RISC-V architecture many-core AI/HPC acceleration chip, built on TSMC’s 7nm process.

Rapidus is a wafer foundry founded in August 2022 with joint investments from eight Japanese companies, including Toyota, Sony, NTT, NEC, SoftBank, Denso, NAND flash giant Kioxia, and Mitsubishi UFJ. Its first factory, “IIM-1,” based in Chitose, Hokkaido, already broke ground in September 2023 and is expected to start running trial production lines in April 2025 and install EUV lithography machines. Rapidus aims to mass-produce the most advanced logic chips below 2nm by 2027.

The initial focus of the cooperation between Rapidus and Esperanto is to enable future semiconductor designers to develop more energy-efficient solutions for AI inference and high-performance computing workloads in data centers and enterprise edge applications. This will help mitigate the unsustainable growth of energy consumption across global data centers.

In 2022, data center, AI, and cryptocurrency consumed about 460 TWh of electricity worldwide in total, comprising 2% of the overall global demand. The International Energy Agency (IEA) predicts that, influenced by factors such as generative AI, global data center power demand could rise to about 1,000 TWh in 2026, roughly equivalent to the entire electricity consumption in Japan.

IEA states that updated regulations and technological improvements, including energy efficiency, are of great significance to curb the surge in data center energy consumption.

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(Photo credit: Rapidus)

In the global landscape of self-developed chips, the industry has predominantly embraced the Arm architecture for IC design. However, Meta’s decision to employ the RISC-V architecture in its self-developed AI chip has become a topic of widespread discussion. It is said the growing preference for RISC-V is attributed to three key advantages including low power consumption, high openness, and relatively lower development costs, according to reports from UDN News.

Noted that Meta exclusively deploys its in-house AI chip, “MTIA,” within its data centers to expedite AI computation and inference. In this highly tailored setting, this choice ensures not only robust computational capabilities but also the potential for low power consumption, with an anticipated power usage of under 25W per RISC-V core. By strategically combining the RISC-V architecture with GPU accelerators or Arm architecture, Meta aims to achieve an overall reduction in power consumption while boosting computing power simultaneously.

Meta’s confirmation of adopting RISC-V architecture form Andes Technology Corporation, a CPU IP and Platform IP supplier from Taiwan, for AI chip development underscores RISC-V’s capability to support high-speed computational tasks and its suitability for integration into advanced manufacturing processes. This move positions RISC-V architecture to potentially make significant inroads into the AI computing market,  and stands as the third computing architecture opportunity, joining the ranks of x86 and Arm architectures.

Regarding the development potential of different chip architectures in the AI chip market, TrendForce points out that in the current overall AI market, GPUs (such as NVIDIA, AMD, etc.) still dominate, followed by Arm architecture. This includes major data centers, with active investments from NVIDIA, CSPs, and others in the Arm architecture field. RISC, on the other hand, represents another niche market, targeting the open-source AI market or enterprise niche applications.
(Image: Meta)

• The continuous AI integration of smart homes accelerates with the Matter protocol.

In the context of the modern era, smart homes are the AI applications that come second only to smartphones and smartwatches. As the penetration rate of smart home devices increases, more and more AI-enabled devices are permeating into human life, ushering in a large-scale era of personalization. The realization of smart homes not only requires smart appliances but also sensors and energy management systems. The deployment of AI will enhance recognition and control.

The diverse application scenarios of smart homes result in a wide variety of products. Despite the vast market size, there is an issue of product ecosystem fragmentation, leading to slow deployment. This can be addressed through the integration of the smart home market via the Matter protocol. As Matter facilitates communication between different devices through software protocols, the importance of software in devices will increase with the product’s AI capabilities, catering to the demands of edge AI applications.

• The RISC-V architecture is on the rise, and the form of MCUs with NPUs will continue to proliferate.

Although CPUs in MCUs are currently dominated by the Arm architecture, open-source RISC-V is gradually rising. In addition to its features such as customization, modularity, and cost-effectiveness, RISC-V is expected to become one of the advantages in smart home applications. It continues to gain support and application from many major manufacturers, expanding the ecosystem of the RISC-V architecture.

Because TinyML models are much smaller than general-purpose AI, they do not require a large amount of computational resources for deployment. This makes them suitable for IoT devices or smart homes that require large-scale deployment, with significant advantages in both technology and cost. Furthermore, with the diverse range of products in smart homes and the increasing demand for product functionality, the form of MCUs equipped with NPUs will become increasingly common as they adapt to the product’s uniqueness and evolve with AI integration.

The US ban on Chinese industries has left China struggling with a seemingly severe shortage of chips. However, China’s tech giants refuse to surrender; instead, they’re pivoting quickly to survive the game.

Since 2019, the US Department of Commerce has added Chinese leading companies like Huawei to its entity list. Restrictions were expanded in 2020 to include semiconductor manufacturing, making a huge impact on SMIC’s advanced processes below 14nm.

Starting in 2021, the US has been intensifying its control by placing more IC design houses on the list, which include Jingjia (GPU), Shenwei (CPU), Loongson Tech (CPU), Cambricon (AI), Wayzim (RF&GPS), and Yangtze (NAND Flash). Furthermore, the export of advanced EDA tools, equipment, CPUs, and GPUs to China has also been banned.

The goal of such measures is to hinder China’s progress in high-tech fields such as 5G/6G, AI, Cloud computing, and autonomous driving by eroding the dominance of its tech giants over time.

China has been aggressively pursuing a policy of domestic substitution in response to the US’s increasing control. As part of this effort, leading domestic IC design companies like Horizon, Cambricon, Enflame, Biren, Gigadevice, and Nations Technologies have been ramping up their efforts for comprehensive chip upgrades in a variety of applications.

Chinese Brands Ramping up for ASICs

There is a particularly intriguing phenomenon in recent years. Since 2019, China’s leading brands have been venturing into chip design to develop highly specialized ASICs (Application Specific Integrated Circuits) at an unprecedented speed. This move is aimed at ensuring a stable supply of chips and also advancing their technical development.

A closer look at how top companies across diverse application fields integrate ASIC chips into their technology roadmap:

• AI Cloud computing: Alibaba, Baidu, Tencent

China’s tech giants are leveraging advanced foundry processes, such as TSMC’s 5nm and Samsung’s 7nm, to produce cutting-edge AI chips for high-end applications like cloud computing, image coding, AI computing, and network chips.

Alibaba launched its AI chip, Hanguang 800, and server CPU, Yitian 710, in 2019 and 2021, respectively. Both chips were manufactured at TSMC’s 5nm process and are extensively used on Alibaba’s cloud computing platform.

In December 2019, Baidu released its AI chip, Kunlun Xin, which uses Samsung’s 14nm process, followed by its 2nd generation, which uses a 7nm process, for AI and image coding.

• Smartphone: Xiaomi, Vivo, OPPO

Due to the high technical threshold of SoC technology used in smartphones, mobile phone brands mainly develop their own chips by optimizing image, audio, and power processing.

In the year of 2021, Xiaomi released the ISP Surge C1, followed by the PMIC Surge P1. Vivo first released the ISP V1 in September 2021, followed by an upgraded product, V1+, in April 2022, and then V2 in November 2022.
OPPO, on the other hand, unveiled the MariSilicon X NPU in December 2021, which enhances the image processing performance of smartphones, using TSMC’s 6nm process, and later revealed the MariSilicon Y Bluetooth audio SoC TSMC’s 6nm RF process later in 2022.

• Home appliance: Konka, Midea, Changhong, Skyworth

The brands are focusing primarily on MCU and PMIC chips that are essential to a wide range of home appliances. They’re also incorporating SoC chips into their smart TVs.

For example, Hisense has jumped into the SoC game in January 2022 by releasing an 8K AI image chip for their smart TVs. Changhong manufactured an MCU with RISC-V architecture and a 40nm process in December 2022.

• Autonomous driving: NIO, Xiaopeng, Li Auto, BYD

The leading companies are developing ISP and highly technical SoC chips for autonomous driving, which has resulted in a slower development process.

In 2020, NIO formed a semiconductor design team for Autonomous driving chips and ISP. Xiaopeng started its Autonomous driving and ISP chip R&D project in the first half of 2021. Li Auto established two subsidiaries in 2022, with a primary focus on power semiconductors and ISP chips.

Finally, BYD, which has a long history of working on MCU and power semiconductor components, also announced its entry into the autonomous driving chip market in 2022.

Navigating the US’ Tech Crackdown

So why are these brands investing so heavily in self-developed ASICs?

One reason is to avoid the risks associated with export control policies from the US and its allies. Developing their own chips would mitigate the risk of supply chain disruptions caused by potential blockades, ensuring a stable supply and the sustainability of their technology roadmap.

In addition, there are many internal incentives for these brands – for instance, companies that have self-developed chips will be eligible for more government subsidies, as this aligns with the government’s aggressive policy to foster the semiconductor industry. Brands can also reduce their reliance on external suppliers by using their own ASIC chips, which can further lower the operating costs.

Technology wise, ASIC chips allow brands to enhance the features they require and enable better integration with the software, which could provide efficiency gains at system level – similar strategies are also being employed by Google and AWS with their AI chips, as well as by Apple with its M1 SoC.

With all things considered, it is certainly possible that we will see a persistent trend of more self-developed ASIC chips made by Chinese brands, which could potentially lead to significant changes in China’s semiconductor supply chain from the ground up.