Microsoft Azure Leads Cloud Innovation with NVIDIA's Blackwell GB200 AI Servers

Microsoft Azure leads in adopting Nvidia's GB200 AI server chips, driving cloud innovation

Microsoft announced on social media that its Azure platform is the first cloud platform to integrate Nvidia's GB200 chip servers, and the team is optimizing every layer of its technology to support the world's most advanced AI models. They also suggested further updates will be revealed at the Microsoft Ignite conference in November. In the global cloud services market, Amazon Web Services (AWS) remains the firm leader, followed by Microsoft Azure in second place, and Google Cloud in third. Since 2023, Microsoft has gained significant momentum, driven by its successful investment in OpenAI, closing the gap with AWS. On October 8, the Microsoft Azure team shared an image on social media showing a server rack housing AI servers powered by Nvidia's GB200 chips. The team is currently fine-tuning its technology stack, leveraging resources like the InfiniBand networking system, industry-leading chips, and advanced closed-loop liquid cooling solutions. Further details will be revealed at the upcoming Microsoft Ignite conference in November. At the last Ignite event, held in November 2023, Microsoft introduced its self-developed chips for general-purpose computing and AI acceleration, used in its data centers. Microsoft CEO Satya Nadella also highlighted the long-standing partnership between Microsoft and Nvidia, emphasizing their collaborative innovation, which continues to drive industry leadership and support the most complex AI workloads. According to Statista, Microsoft and Meta were the top two buyers of Nvidia's H100 chips in 2023, followed by other major companies like Google, Amazon, Oracle, and Tencent. Recently, cloud platform providers have focused their promotions on the continuous adoption of cutting-edge computing resources. They now offer a variety of computing options, including GPUs and in-house developed proprietary chips. Shortly after Nvidia launched its Blackwell platform in late March, AWS announced its support for Blackwell GPUs and its integration into the joint Project Ceiba supercomputer initiative. Google Cloud also revealed that its AI Hypercomputer would incorporate Blackwell GPUs, with services set to launch in 2025 via virtual machines (VMs). Data from Google Cloud shows that many customers, including startups like Character.ai, use both Google Cloud TPUs and Nvidia GPUs to meet their AI training and inference needs. In June, Apple announced progress on its foundational models, revealing that it had used a combination of Google TPUs, cloud-based GPUs, and on-premises GPUs during the model pre-training phase. The growing demand for computing power has also prompted many Taiwanese companies to invest in building data centers and supercomputing facilities. Alongside collaborations between chipmakers and server manufacturers, software companies are transforming by offering new services such as GPU partitioning, computing power leasing, and management solutions. However, some software companies believe that the strength of cloud platforms lies in their financial resources, which allow them to stay on top of the latest GPU technologies. Yet, only a limited number of companies -- mainly international cloud, network, and AI developers -- actually require the latest GPUs. For most small and medium-sized enterprises (SMEs) in Taiwan, the real challenge lies in managing hybrid computing resources (including older GPUs) and ensuring compatibility between software and hardware systems. Companies have also noted that, due to concerns over data privacy and budget constraints, some users are moving part of their workloads from the cloud back to on-premises infrastructure.

Microsoft Azure To Be The First Cloud Platform Running NVIDIA Blackwell "GB200" AI Servers

Microsoft has said that its Azure cloud platform will be the first in the world to be running NVIDIA's brand new Blackwell GB200 AI servers. Microsoft today showed off its newly built NVIDIA's Blackwell GB200-powered server for the Azure AI cloud computing platform. The official handle of Microsoft Azure posted that they are the first cloud system having GB200-powered AI servers for scaling advanced AI models. Microsoft Azure offers its customers services like virtual machines, AI processing, etc. for managing the applications. This allows its users to scale and upgrade their applications without owning the hardware themselves. With the usage of the latest NVIDIA Blackwell B200 GPUs, Azure is enhancing user experience by offering its users higher performance than ever. The GB200-powered AI servers will utilize the flagship data center B200 GPUs, which utilize the GB200 die and offer 192 GB of HBM3e memory. The GPU is a high-performance chip aimed at advanced and heavy workloads such as deep learning, training large AI models, and processing large datasets while being more efficient than its predecessors. Through the usage of B200 GPUs, the AI models can be trained faster at Azure, ensuring its leading performance among all other cloud computing platforms. As shown in the picture, the company has a server rack with several B200 GPUs. We don't know how many B200 GPUs are used inside this server and how many of these the company has deployed yet. The server is being cooled by liquid cooling solutions to maintain lower temperatures, which looks like the initial test phase by Microsoft to see how to implement liquid cooling for commercial servers. It should be kept in mind that the shown server isn't GB200 NVL72, which NVIDIA has prepared for leveraging the power of 36 Grace CPUs and 72 B200 GPUs. That rack is insanely powerful for building a powerful platform that can yield up to 3240 TFLOPS of FP64 Tensor Core performance and is going to be used in Taiwan's fastest supercomputer by Foxconn. We recently reported about OpenAI showing off the DGX B200 system on X and looks like many more are joining the race to use NVIDIA's Blackwell chips.

These are the first servers that will feature Nvidia's new AI GB200 graphics cards - Softonic

Microsoft has stated that its Azure platform will be the first in the world to run NVIDIA's new Blackwell GB200 AI servers Microsoft has showcased today its new Blackwell GB200 server from NVIDIA for the Azure AI cloud computing platform. And if this sounds strange to you, we'll explain it. The official Microsoft Azure management has announced that it is the first cloud system to feature AI servers with GB200 technology to scale advanced AI models. Microsoft Azure offers its customers services such as virtual machines, AI processing, etc. to manage applications. This allows users to scale and update their applications without the need to own the hardware. With the use of the latest NVIDIA Blackwell B200 GPUs, Azure is enhancing the user experience by providing more performance than ever before. The AI servers powered by GB200 will use the B200 GPUs, the flagship of the data center, which utilize the GB200 array and offer 192 GB of HBM3e memory. The GPU is a high-performance chip designed for advanced and heavy workloads, such as deep learning, training large AI models, and processing large datasets, being more efficient than its predecessors. Thanks to the use of B200 GPUs, AI models can be trained faster on Azure, ensuring their leading performance among all other cloud computing platforms. As seen in the tweet image, the company has a server rack with several B200 GPUs. We do not know how many B200 GPUs are used in this server nor how many of them the company has already deployed. The server is being cooled by liquid cooling solutions to maintain lower temperatures, which appears to be the initial testing phase for Microsoft to see how to implement liquid cooling in commercial servers. It should be noted that the server shown is not the GB200 NVL72, which NVIDIA has prepared to leverage the power of 36 Grace CPUs and 72 B200 GPUs. That rack is incredibly powerful for building a robust platform that can produce up to 3240 TFLOPS of FP64 Tensor Core performance and will be used in Taiwan's fastest supercomputer by Foxconn.