NVIDIA Presents AI Cloud Provider Reference Architecture

 

A new reference architecture from NVIDIA is available to cloud providers who wish to provide their clients with generative AI services. 

 

Large language models (LLMs) and generative artificial intelligence (AI) may be handled by data centers constructed with high speed, scalability, and security thanks to the NVIDIA Cloud Partner reference design.

 

The standard architecture, which also ensures compatibility and interoperability across various hardware and software components, enables the NVIDIA Partner Network's NVIDIA Cloud Partners to deliver AI solutions more rapidly and inexpensively. 

 

The architecture will also help cloud providers meet the growing demand for AI services from many industries and company types that want to deploy generative AI and LLMs without having to invest in infrastructure.

 

 

Thanks to generative AI and LLMs, organizations are transforming the way they approach challenging problems and generate new value. These technologies use deep neural networks to generate text, images, audio, and video that are realistic and unique based on a particular input or context.

 

Chatbots, copilots, and other content generation are only a few of the uses for generative AI and LLMs.

 

But since cloud providers have to supply the technology and software required to manage these workloads, generative AI and LLMs also present a lot of difficulties.

 

For the technologies to function at their fastest and most efficient, enormous quantities of processing power, storage, and network bandwidth are needed, in addition to specialized gear and software.

 

 

For example, LLM training necessitates a high number of GPU servers working together and continually communicating with storage systems and each other.

 

 This translates to north-south and east-west traffic in data centers, necessitating high-performance networks for prompt and efficient communication.

 

Similar to this, many GPUs must cooperate to handle a single query for generative AI inference with bigger models.

 

Additionally, because cloud providers cater to a variety of clients with varying needs and expectations, they must guarantee the security, dependability, and scalability of their infrastructure. Along with providing support and upkeep for their services, cloud providers must also adhere to industry standards and best practices.

 

These issues are addressed by the NVIDIA Cloud Partner reference architecture, which offers cloud providers a complete, full-stack hardware and software solution to enable AI services and processes for various use cases.

 

 The reference architecture is based on NVIDIA's years of expertise planning and constructing large-scale installations for clients as well as internally. It consists of:

 

 

GPU servers using NVIDIA's most recent GPU architectures—Hopper and Blackwell, for example—that offer unmatched computing power and performance for AI applications are available from NVIDIA and its manufacturing partners.

 

storage options include high-performance storage designed for applications like AI and LLM from vetted partners. Furthermore, NVIDIA DGX Cloud and NVIDIA DGX SuperPOD compatibility has been verified and tested for the products. They've shown to be scalable, trustworthy, and efficient.

 

GPU servers can communicate quickly and effectively with one other thanks to the high-performance east-west network offered by NVIDIA Quantum-2 InfiniBand and Spectrum-X Ethernet networking.

 

NVIDIA BlueField-3 DPUs, which provide zero-trust security, elastic GPU compute, and data storage acceleration in addition to providing high-performance north-south network connectivity.

AI data center infrastructure provisioning, monitoring, and management tools and services are offered by NVIDIA and its management partners through in-band and out-of-band management solutions.

Software from NVIDIA AI Enterprise, such as: 

Cloud providers may manage and supply their servers with the aid of NVIDIA Base Command Manager Essentials.

 

The NVIDIA NeMo framework aids in the training and optimization of generative AI models by cloud providers.

A collection of user-friendly microservices called NVIDIA NIM is intended to speed up the implementation of generative AI in business settings.

For speech services, use NVIDIA Riva.

 

Workloads involving Spark will be accelerated via the NVIDIA RAPIDS accelerator.

 

The NVIDIA Cloud Partner reference design provides cloud providers with the following main advantages:

 

 

Build, Train, and Go: NVIDIA infrastructure experts physically deploy and provision the cluster using the architecture to expedite cloud provider rollouts.

 

Accelerated deployment of AI products through the utilization of NVIDIA and partner supplier knowledge and best practices can give cloud providers a competitive advantage in the market. This can be achieved through the architecture.

Superior Performance: The architecture is optimized and benchmarked using industry-standard benchmarks to deliver optimal performance for AI activities.

 

Scalability: Because AI systems are built for cloud-native settings, it is easier to create flexible, scalable AI systems that can grow to satisfy end users' rising expectations.

 

Interoperability: The design makes sure that each component may function with any other component, simplifying communication and integration.

 

Maintenance and support: NVIDIA Cloud Partners can contact NVIDIA subject matter experts for assistance with unforeseen issues that may come up both during and after deployment.