Newsletter #33- Nvidia and Microsoft Partner to Accelerate AI Innovation with New Hardware and Software Offerings

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The landscape of artificial intelligence (AI) is rapidly evolving, driven by advancements in hardware and software that are enabling new and groundbreaking applications. At the recent Microsoft Ignite conference, Nvidia and Microsoft made a series of announcements that underscore their commitment to accelerating AI innovation and propelling the industry forward.

NVIDIA AI Enterprise Software Integrated with Azure Machine Learning

In a move to streamline AI development and deployment, Nvidia announced that its NVIDIA AI Enterprise software suite will be integrated with Azure Machine Learning. This integration will provide Azure customers with direct access to Nvidia's comprehensive suite of AI frameworks, libraries, and tools, empowering them to build, train, and deploy AI models.

NVIDIA DGX Cloud Now Available on Microsoft Azure Marketplace

NVIDIA also unveiled the availability of NVIDIA DGX Cloud on the Microsoft Azure Marketplace. DGX Cloud is a cloud-based AI supercomputing platform that provides developers and researchers with instant access to powerful AI infrastructure. With DGX Cloud on Azure, organizations can accelerate their AI workloads and bring their innovations to market faster.

Generative AI Foundry Service on Microsoft Azure

To further support the development of generative AI applications, Nvidia introduced the Generative AI Foundry Service on Microsoft Azure. This new service provides a comprehensive set of tools and expertise to help enterprises and startups develop, train, and deploy custom generative AI models.

New H100 and H200 Tensor Core GPU Instances Coming to Microsoft Azure

Recognizing the growing demand for high-performance AI compute, Microsoft announced that it will be adding new H100, H200-based virtual machines to Azure. These new instances will provide Azure customers with the latest in AI acceleration technology, enabling them to tackle even the most demanding AI workloads.

Key Features of the Nvidia H200 Tensor Core GPU

• 141GB of HBM3e memory: The H200 is the first GPU to feature HBM3e memory, which provides 2.4x more bandwidth compared to its predecessor, the H100. This increased bandwidth enables the H200 to handle even the most demanding AI workloads.
• 4.8 terabytes per second (TB/s) of memory bandwidth: The H200's 4.8 TB/s of memory bandwidth is the highest of any GPU available today. This makes it ideal for applications that require high memory bandwidth, such as generative AI and LLMs.
• Increased performance: The H200 delivers up to 1.4x faster performance than the H100 for a variety of AI workloads.
• Improved energy efficiency: The H200 is up to 5x more energy efficient than the H100, making it a more cost-effective solution for data centers.

AI Hardware Roadmap:

These announcements from Nvidia and Microsoft align with the broader AI hardware roadmap, which is characterized by increasing compute power, memory bandwidth, and interconnect speeds. The new H100 and H200 Tensor Core GPUs are examples of this trend, offering significant performance improvements over previous generations. Additionally, the availability of AI infrastructure on cloud platforms like Azure is making it easier for organizations to access the resources they need to develop and deploy AI applications.

These new hardware and software offerings will undoubtedly have a significant impact on the development and deployment of AI applications, paving the way for a future powered by artificial intelligence.

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