Original ChatGPT training requires large-scale parallel connection of high-performance chips, and high-speed interface IP meets the dividend era

In recent years, the boom of ChatGPT has rekindled the boom of AI industry, especially in the field of AIGC (which refers to the use of AI technology to generate content), which has entered into a frenzy. The head technology enterprises are scrambling for the first time to release ChatGPT-like applications.
As we all know, ChatGPT-like applications are a gold gobbler. Microsoft used 10000 high-end GPUs of Yingweida Zhang to train ChatGPT. "From the perspective of training, if GPU chips with better computing performance, such as A100, cannot be clustered together for training, then it may take hundreds of years to train a big model like ChatGPT. Therefore, the training of AI big model is a huge challenge to high-speed interface IP, and also a huge opportunity." Tang Rui, vice president of market and strategy of Kuixin Technology, said in an interview with e-enthusiast.
Kuixin Technology was founded in 2021. The company's slogan is "high-speed interconnection of cores and particles, a source of massive computing power". At present, the high-speed interface IP combination that Quixon has launched includes USB, PCIe, SATA, SerDes, MIPI, DDR, HDMI, DP, HBM and other rich types.
ChatGPT-like driving the development of interface IP
From the perspective of semiconductor industry distribution, IP is the underlying technology, and so is the interface IP. Therefore, the key and importance are self-evident. So what role can interface IP play in AIGC industry? Tang Rui mentioned the following points.
First, the interconnection interface on the chip, that is, the interconnection interface IP of Die to Die type, including UCIE, is used to expand the computing capacity of a single chip; Secondly, the interconnection interface IP of Chip to Chip type, including SerDes/PCIE/CXL, can speed up the interconnection and data exchange between chips to meet the needs of higher bandwidth; In addition, there are memory interface IP, including SATA, DDR, HBM, etc., which can be used to create higher performance storage products and help ChatGPT-like storage and exchange large-scale data; The next layer is the interface IP of the data communication interface. Therefore, from the perspective of training, the explosion of ChatGPT-like applications can bring very large demand for interface IP.
In the previous forecast, data from market research institutions showed that the market size of high-speed Internet IP is expected to grow rapidly at a compound annual growth rate of 75% from 2022 to 2026. "The growth of the interface IP market must follow the general trend of the whole high-performance computing chip, including the improvement of chip computing performance, memory and bandwidth needs the help of interface IP, so the increase of chip usage will certainly lead to greater interface IP usage." Tang Rui believes that, "At the same time, the improvement of the performance of computing chips has been limited by the slowdown of Moore's Law, and the performance of single chips will gradually encounter bottlenecks, so the interconnection of computing power cluster is an effective means, which will also accelerate the development of interface IP."
Although the industry boom is coming, Tang Rui is not worried about the influx of many peers or friends at once, which will cause the domestic interface IP industry to be involved. "The intensity of market competition will increase, but interface IP is a high-threshold field. At present, there are not many domestic talents to do high-speed hybrid circuits, especially those who do high-speed analog circuit design in advanced manufacturing processes. Therefore, it is very difficult to enter this field from scratch." He said.
Layout and catch-up of domestic manufacturers
From the perspective of global industrial structure, in terms of interface IP, at present, EDA manufacturers such as Xinsi Technology and Kaideng Electronics and other international interface IP manufacturers are still in the leading position. Relevant data shows that by 2021, the self-sufficiency rate of domestic interface IP is still less than 10%.
"At present, from the technical point of view, the domestic interface IP manufacturers are still in the catch up position, but the gap has become smaller and smaller." Tang Rui pointed out that "in 2023, Quixon Technology will launch a series of interface IP products with internationally leading performance, including HBM3 and other leading D2D type of interconnection interface IP."
At the same time, he also said that in terms of serving domestic customers, there will actually be a lot of local needs, which need to be combined with the process characteristics of the wafer factory to provide IP solutions. Many IP products of Quixon Technology have received inquiries from customers in the process of research and development or before research and development. They have very clear requirements around the customer's chip architecture. Quixon Technology has established several industrial alliances with its downstream customers. Through these alliances, different types of computing chip companies are united to develop in a coordinated manner, and domestic solutions are built around data center applications to fill the gap in China.
At present, the computing power cluster used in AI large model training is basically built based on Nvidia universal computing power chips. In this regard, there is still a certain performance gap between domestic universal computing power chips. Tang Rui said that there are still opportunities for domestic high-performance computing chips. The AI big model is not a new thing in recent years. In recent years, the domestic AI industry has been following this trend, but the big model parameters behind ChatGPT-like applications are larger. In response to this demand, the domestic chip industry has also started the layout of this aspect for a long time, including the interface IP circuit where Quixon Technology is located, which is working in this direction. However, there will be a time difference between IP R&D, chip design and application landing. In fact, foreign companies are also using the previous chips to provide hardware support in this area through interconnection.
"It also needs to be pointed out that AIGC is a combination of software and hardware. In terms of software, the volume of algorithm model is also a direction worthy of research and breakthrough. At present, the GPT algorithm of Open AI is not the only open source AIGC algorithm in foreign countries. According to the introduction information, there are also some models with smaller parameters that can realize ChatGPT-like applications. We can actually use these models for reference to reduce the demand of software for hardware Pressure. " Tang Rui finally said.
Summary
IP has great leverage on the semiconductor industry. Worldwide, the IP sales of more than US $6 billion drive the global semiconductor market sales of US $500 billion. For domestic chips, it is very difficult to achieve a single chip performance explosion in the short term. However, through high-speed interface IP and computing power cluster, it can also gradually enter the ChatGPT-like dividend market.

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