{"id":162830,"date":"2025-08-14T16:51:05","date_gmt":"2025-08-14T16:51:05","guid":{"rendered":"https:\/\/teknomers.com\/en\/he-has-discovered-a-method-to-boost-chinas-competitiveness-in-the-face-of-the-united-states\/"},"modified":"2025-08-14T16:51:07","modified_gmt":"2025-08-14T16:51:07","slug":"he-has-discovered-a-method-to-boost-chinas-competitiveness-in-the-face-of-the-united-states","status":"publish","type":"post","link":"https:\/\/teknomers.com\/en\/he-has-discovered-a-method-to-boost-chinas-competitiveness-in-the-face-of-the-united-states\/","title":{"rendered":"He has discovered a method to boost China’s competitiveness in the face of the United States."},"content":{"rendered":"\n

Two days ago, we shared exciting news: the Chinese state media outlet, Securities Times, revealed that Huawei was set to unveil a groundbreaking technological advancement aimed at \u00a0reducing China’s dependence\u00a0 on foreign HBM memory chips (\u00a0High Bandwidth Memory\u00a0). According to this source<\/a>, Huawei was expected to make an official announcement during the Applications Forum and Development of Financial Reasoning 2025 in Shanghai.<\/p>\n

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Huawei has indeed fulfilled its promise, albeit not in the manner many anticipated. It is vital to recognize that \u00a0Chinese chip manufacturers are currently unable to produce solutions that rival the cutting-edge memories\u00a0 developed by South Korean giants Samsung and SK Hynix, as well as American firm Micron Technology. Graphics Processing Units (GPUs) require robust HBM memory chips to function optimally, which implies that their performance is significantly influenced by these memory components.<\/p>\n

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According to the editors of SEMIANALYSIS<\/a>, the total bandwidth of HBM3 memory chips used in conjunction with some of the most advanced GPUs from NVIDIA and AMD exceeds \u00a0819 GB\/s\u00a0. In contrast, DDR5 and GDDR6X memories only reach comparatively modest speeds of \u00a070.4 GB\/s\u00a0 and \u00a096 GB\/s\u00a0, respectively. Future iterations, such as HBM3E and HBM4, promise even greater capabilities. Currently, Chinese manufacturers do not produce HBM memory of this caliber, but Huawei\u2019s recent announcement aims to change this landscape.<\/p>\n

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An Algorithm Expressly Designed to Accelerate Inference in AI<\/h2>\n

Leaks surfaced just \u00a048 hours\u00a0 before the announcement suggested that Huawei might reveal a cutting-edge packaging technology that could rival those employed by SK Hynix, Samsung, or Micron in the production of their HBM3 and HBM3E memories. The manufacturing process for these integrated circuits is complex, necessitating multiple stacked DRAM chips and an interface connecting the \u00a0Extended Processing Unit (XPU)\u00a0 with the densely packed HBM memory chips. For instance, the HBM3E stack utilizes over \u00a01,000 drivers\u00a0 to link the XPU and HBM memory.<\/p>\n

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 <img alt=\"When the stars were formed, it has always been one of the greatest mysteries in the universe. And we are closer to solving it\" width=\"375\" height=\"142\" src=\"https:\/\/i.blogs.es\/32b524\/estrellas-ap\/375_142.jpeg\"\/><\/code><\/pre>\n<\/div>\n<\/div><\/div>\n<\/div>\n
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According to Huawei, the UCM algorithm is capable of drastically accelerating inference in the great AI models<\/p>\n<\/p><\/div>\n<\/div>\n
However, Huawei ultimately introduced a different technology: an advanced algorithm known as \u00a0UCM (Unified Cache Manager)\u00a0. According to the company, this algorithm can \u00a0drastically accelerate inference\u00a0 in large artificial intelligence models. Notably, inference refers to the computational process employed by language models to generate responses corresponding to the requests they receive.<\/p>\n
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To optimize its functionality, the UCM algorithm employs a clever strategy: it determines the appropriate memory type for data storage based on latency requirements. In practical terms, this algorithm functions as a massive cache, ensuring that each piece of data is directed to the suitable memory type, including HBM3, to minimize latency during inference. If a specific data point is frequently accessed, it will be stored in a high-speed memory format, such as HBM3. According to Huawei<\/a>, this technology can reduce inference latency by an impressive \u00a090%\u00a0. Intriguingly, the company plans to release the UCM Source Open Algorithm in September.<\/p>\n
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For additional insights, refer to SCMP.<\/a> <\/p>\n
As the tech industry grapples with the implications of Huawei’s announcement, it remains to be seen how this algorithm will affect the balance of power in AI technology and memory manufacturing. The move signifies an ambitious attempt to lessen China\u2019s reliance on foreign technology while enhancing its capability to innovate independently. This shift could reshape the future of AI development within the country and foster a new wave of competitive advancements in the memory chip market.<\/p>\n

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General News – 2<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
Two days ago, we shared exciting news: the Chinese state media outlet, Securities Times, revealed that Huawei was set to unveil a groundbreaking technological advancement aimed at \u00a0reducing China’s dependence\u00a0 on foreign HBM memory chips (\u00a0High Bandwidth Memory\u00a0). According to this source, Huawei was expected to make an official announcement during the Applications Forum and […]<\/p>\n","protected":false},"author":1,"featured_media":162090,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[36399],"tags":[2630,323,12758,4180,1866,9357,611,610],"class_list":["post-162830","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology","tag-boost","tag-chinas","tag-competitiveness","tag-discovered","tag-face","tag-method","tag-states","tag-united"],"_links":{"self":[{"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/posts\/162830","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/comments?post=162830"}],"version-history":[{"count":0,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/posts\/162830\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/media\/162090"}],"wp:attachment":[{"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/media?parent=162830"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/categories?post=162830"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/tags?post=162830"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}