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Data Center Knowledge更新于 10月22日 00:13

Nvidia 发布 DSX Pod 预制 AI 数据中心模块

Nvidia Unveils DSX Pod for Faster AI Data Center Builds

AI 导读

Nvidia 在 GTC Berlin 发布 DSX Pod 集装箱式 AI 数据中心模块,内置 7 个 Vera Rubin NVL72 机架及网络、布线和冷却系统,称在已准备好的站点可将部署时间从约 6 个月缩短至最快 14 天。该产品面向需要快速上线大规模 AI 算力的机构,Nvidia 正与 Bull、Dell、HPE、Lenovo、Eaton、Schneider Electric、Vertiv 等 17 家合作伙伴推进,计划于 2027 年初上市。Nvidia 同时公布供应链扩产计划,未来三年基板产能提升 2.5 倍,到 2028 年先进封装产能扩大 300% 以上。

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AI 评分 61

原文给出了预制模块的部署时间对比和合作方名单,读者可据此判断 AI 数据中心交付方式的变化。

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Nvidia said the DSX Pod, a prebuilt containerized AI data center, reduces deployment time from six months to 14 days.Wylie Wong,Chips and Hardware Writer

October 21, 20263 Min ReadThe Nvidia DSX Pod.Nvidia

Nvidia today introduced DSX Pod, a containerized AI data center module that comes with seven Vera Rubin NVL72 racks, along with networking, cabling, and cooling already installed. The company says the design can cut deployment time at a prepared site from roughly six months to as little as 14 days.

Announced at GTC Berlin, the modular offering is aimed at organizations that need to bring large amounts of AI compute online more quickly without going through the full planning, construction, and labor demands of a traditional on-site build. Nvidia said it is working with 17 partners, including Bull, Dell Technologies, HPE, Lenovo, Eaton, Schneider Electric, and Vertiv, to make DSX Pod available in early 2027.

“This is a fully assembled, fully tested, fully pre-plumbed, prebuilt, pre-validated container that is the building block for AI factories,” said Ian Buck, Nvidia’s vice president of hyperscale and high-performance computing, in a media briefing. “It’s designed to accelerate Europe’s infrastructure deployment and dramatically shorten the time to first token.”

Although Nvidia unveiled the reference design in Berlin, Buck said the container is intended for worldwide deployment. He said the company chose GTC Berlin for the announcement because it sees modular, faster-to-deploy infrastructure playing an important role in Europe’s expansion of AI capacity.

Buck said the product is designed for organizations that want to bring compute online at the hundreds-of-megawatts scale more quickly while reducing the complexity of a conventional site build.

Ashish Nadkarni, an IDC analyst, said the DSX Pod could be appealing for three use cases: sovereign AI deployments that require physical isolation, smaller-footprint AI deployments built for specific needs, and edge AI environments.

“It provides accelerated compute capacity in a turnkey fashion wherever there is demand,” Nadkarni said.

The DSX Pod announcement came alongside a broader Nvidia update on manufacturing expansion. To support the growing demand for AI infrastructure, Nvidia and its supply chain partners said they plan to increase substrate capacity by 2.5 times over the next three years, expand advanced packaging capacity by more than 300% by 2028, and increase optical engine capacity for co-packaged optics by 15 times by mid-2027, with a goal of doubling that again by the end of 2028.

Nvidia also used the event to highlight software and security controls for AI deployments at scale. The company introduced the OpenShell Reference Architecture, which it said is designed to help organizations govern AI agents by defining what they can access and do, monitoring their behavior, and enforcing policies if unsafe activity is detected.

Justin Boitano, Nvidia’s vice president of enterprise, said the architecture combines Vera Rubin NVL72 infrastructure for training and inference with Nvidia Vera systems that run and govern the “agent harness.” BlueField DPUs act as an isolated security monitor between the two systems, inspecting traffic and enabling policy updates that can disconnect an agent if unsafe behavior is detected.

Nvidia said companies using the OpenShell Reference Architecture to strengthen agent security include Anthropic, AWS, Google Cloud, Meta, Microsoft, OpenAI, and Perplexity.

Wylie Wong is a journalist and freelance writer specializing in technology, business and sports. He previously worked at CNET, Computerworld and CRN and loves covering and learning about the advances and ever-changing dynamics of the technology industry. On the sports front, Wylie is co-author of Giants: Where Have You Gone, a where-are-they-now book on former San Francisco Giants. He previously launched and wrote a Giants blog for the San Jose Mercury News, and in recent years, has enjoyed writing about the intersection of technology and sports.See more from Wylie Wong

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