NVIDIA has recently launched the MGX server specification, a reference architecture that allows manufacturers to create a variety of servers for different applications, such as artificial intelligence, high-performance computing, and Omniverse workloads.



The MGX-based designs can be produced in over 100 variants, resulting in a reduction of development costs by up to 75% and development time to just six months. Companies such as ASRock Rack, ASUS, GIGABYTE, Pegatron, QCT, and Supermicro are among those who have adopted the MGX server specification.

Manufacturers using this specification can build systems that are optimized for accelerated computing, then select the specific GPU, DPU, and CPU that suits their needs. Such flexibility allows for customizations to cater to different applications, including data science, graphics, and video processing, and design and simulation. The incorporation of MGX ensures that hardware enhancements can be implemented seamlessly for future generations. Additionally, the MGX server specification is compatible with cloud and enterprise data centers.

QCT and Supermicro will be among the first companies to develop MGX-based designs, while SoftBank Corporation plans to employ the specification in its hyperscale data centers across Japan. With MGX, SoftBank Corporation aims to address cost-effectiveness and allocate GPU resources between generative AI and 5G applications.

The MGX server specification is distinct from NVIDIA HGX, which is optimized for AI and HPC systems with scalable multi-GPU configurations. MGX offers cross-generational compatibility with NVIDIA products, enabling manufacturers to implement next-generation products without costly redesigns. Data centers can meet their computing demands while balancing their ecological footprint and operating expenses, thanks to the superior performance and energy efficiency of NVIDIA's accelerated computation servers.

NVIDIA's MGX server specification is designed to enable cost-effective construction of servers for artificial intelligence (AI) workloads. The specification focuses on providing a scalable and efficient platform for deploying GPUs in a server environment.

One of the key features of the MGX server specification is its flexibility in terms of GPU configuration. It allows for the installation of multiple GPUs, making it suitable for various AI workloads that require high-performance computing. This flexibility not only enables faster and more efficient processing but also allows for better utilization of resources.

The MGX server specification also emphasizes energy efficiency and high-density compute capabilities. By optimizing power consumption, it helps reduce operational costs associated with running AI workloads. Moreover, the high-density compute capabilities enable users to maximize the number of servers they can fit into a given data center space.

In addition, the MGX server specification provides guidelines for server design, thermal management, power distribution, and other aspects related to server construction. These guidelines ensure that the servers meet quality standards and can be easily integrated into existing infrastructures.

By following the MGX server specification, organizations can construct cost-effective servers that are specifically tailored for AI workloads. This specification from NVIDIA is an important contribution to the AI ecosystem, enabling efficient and scalable deployment of GPUs in server environments.

Quote from: Hosting News on Jun 05, 2023, 02:18 AMNVIDIA has recently launched the MGX server specification, a reference architecture that allows manufacturers to create a variety of servers for different applications, such as artificial intelligence, high-performance computing, and Omniverse workloads.



The MGX-based designs can be produced in over 100 variants, resulting in a reduction of development costs by up to 75% and development time to just six months. Companies such as ASRock Rack, ASUS, GIGABYTE, Pegatron, QCT, and Supermicro are among those who have adopted the MGX server specification.

Manufacturers using this specification can build systems that are optimized for accelerated computing, then select the specific GPU, DPU, and CPU that suits their needs. Such flexibility allows for customizations to cater to different applications, including data science, graphics, and video processing, and design and simulation. The incorporation of MGX ensures that hardware enhancements can be implemented seamlessly for future generations. Additionally, the MGX server specification is compatible with cloud and enterprise data centers.

QCT and Supermicro will be among the first companies to develop MGX-based designs, while SoftBank Corporation plans to employ the specification in its hyperscale data centers across Japan. With MGX, SoftBank Corporation aims to address cost-effectiveness and allocate GPU resources between generative AI and 5G applications.

The MGX server specification is distinct from NVIDIA HGX, which is optimized for AI and HPC systems with scalable multi-GPU configurations. MGX offers cross-generational compatibility with NVIDIA products, enabling manufacturers to implement next-generation products without costly redesigns. Data centers can meet their computing demands while balancing their ecological footprint and operating expenses, thanks to the superior performance and energy efficiency of NVIDIA's accelerated computation servers.

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