Chinese technology conglomerate Alibaba Group Holdings has unveiled a new in-house processing chip that will be used to power servers in its data centres.
Soon after the announcement, the company’s shares on The Stock Exchange of Hong Kong jumped almost 2% higher to HKD165.9 ($21.33) before shedding some of those gains to settle at HKD164 during mid-day trading.
The server chips, named Yitian 710, have been custom-built by the company’s chip development unit T-Head. It has been built using the advanced 5-nanometer process technology and micro-architecture developed by SoftBank-backed chip designer Arm. The processor will not be available for use outside of Alibaba.
Alibaba looks to global computing market
“Customising our own server chips is consistent with our ongoing efforts towards boosting our computing capabilities with better performance and improved energy efficiency. We plan to use the chips to support current and future businesses across the Alibaba Group ecosystem,” said Jeff Zhang, president of Alibaba Cloud Intelligence, in a statement.
“Together with our global partners, including Intel, Nvidia, AMD and Arm, we will continue to innovate our compute infrastructure and offer diverse computing services for our global customers,” he added.
According to market research firm Gartner, Alibaba is the third-largest cloud computing service provider in the world, behind only Amazon and Microsoft. It had a global market share of 9.5% in 2020, making it the largest cloud computing service provider in China, well ahead of Huawei.
Aiming for the next generation of cloud services
Besides unveiling its chip, Alibaba Cloud Intelligence also announced the development of proprietary servers called Panjiu. According to the statement, Panjiu was developed for the “next-generation of cloud-native infrastructure.”
“With a modular design approach for large-scale data centre deployment, these servers are expected to deliver exceptional economic value for a variety of cloud-native workloads, such as containerised applications and computed optimised workloads,” the statement added.