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China’s Communist Party
ChinaPolitics

China’s new data agency plans fast track to powerful national computing network

  • China – second only to the US in terms of aggregated processing power – sets 2025 deadline to scale up capacity by half
  • At first work conference since its formation last year, NDA vows to spend government funds well as it connects regional computing centres

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China’s national data network aims to address digital imbalances between the more prosperous areas of eastern China and the energy-rich west. Shutterstock
Jane Caiin Beijing
China will accelerate construction of a nationwide integrated computing power network, its top data regulator vowed at its first annual meeting as Beijing seeks to boost innovation in a technology competition with the United States.
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At the two-day national data work conference which ended on Tuesday, National Data Administration (NDA) head Liu Liehong vowed to “optimise data infrastructure distribution” and “accelerate construction of the computing power network”.

“We are working to improve the distribution of general purpose, intelligent and supercomputing power, increase the synergy of east-middle-west regions, support the integration of computing power and green electricity, as well as balance between its development and security,” he said, according to an NDA post on social media platform WeChat.

The conference took place just months after the NDA was inaugurated at the end of October, in response to President Xi Jinping’s calls to drive digital development and innovation in a competition with the US for hi-tech dominance.

The nationwide computing power network, which will be up and running by next year, is designed to unite computing centres across the country, addressing regional digital imbalances between the more prosperous areas of eastern China and the energy-rich west, the NDA has said.

China, which is second only to the US in aggregated computing power, aims to scale up its capacity by half by 2025. Demand for computing power, particularly the GPU power necessary for artificial intelligence learning, has been surging in recent years.

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