China's Huawei Technologies Co. is poised to make significant strides in the artificial intelligence (AI) semiconductor industry with its latest development, the 910C Graphics Processing Unit (GPU). According to sources cited by Reuters, Huawei has successfully engineered a chip that rivals the performance of Nvidia's H100 AI chip and is preparing to supply it to customers in large quantities as early as next month.
The 910C GPU represents an architectural advancement, doubling the computing power and memory capacity of its predecessor, the 910B. This development comes amid stringent U.S. export controls aimed at limiting China's access to advanced semiconductors, citing concerns over their potential military applications.
Huawei has reportedly distributed samples of the 910C to technology companies since the end of last year, and orders have already been placed. However, the company has remained tight-lipped about the delivery schedule and performance details of the 910C.
The United States has been restricting China's access to advanced semiconductors, banning exports of Nvidia's H100 to China even before its 2022 release. In response, Nvidia began producing a lower-spec version, the H20, for the Chinese market. However, recent decisions by the U.S. Department of Commerce to restrict H20 exports have created an opportunity for Huawei's Ascend 910C GPU to become the preferred hardware for AI development among Chinese companies.
While it remains unclear which company will primarily produce the 910C, reports suggest that Semiconductor Manufacturing International Corporation (SMIC) in China is involved in manufacturing key components. Despite low yield rates, some components reportedly utilize semiconductors from Taiwan's TSMC for Huawei's Chinese customer Sophgo. Huawei has denied using TSMC semiconductors, and TSMC has stated it complies with regulations, ceasing supplies to Huawei since September 2020.
This development highlights the ongoing semiconductor tensions between the U.S. and China, as Huawei continues to push the boundaries of AI chip technology amid regulatory challenges.
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