NVIDIA Unveils Reference Architecture for AI Cloud Providers

Jakarta, INTI - NVIDIA has announced a new reference architecture for cloud providers who want to offer generative AI services to their customers. This reference architecture is a blueprint for building high-performance, scalable, and secure data centers that can handle generative AI and large language models (LLMs).

The reference architecture allows NVIDIA Cloud Partners within the NVIDIA Partner Network to reduce the time and cost of deploying AI solutions while ensuring compatibility and interoperability among various hardware and software components.

Benefits of NVIDIA's Reference Architecture

This architecture helps cloud providers meet the growing demand for AI services from organizations of all sizes and industries that want to leverage the power of generative AI and LLMs without investing in their own infrastructure.

Generative AI and LLMs are transforming how organizations solve complex problems and create new value. These technologies use deep neural networks to generate realistic and novel outputs, such as text, images, audio, and video, based on a given input or context. Generative AI and LLMs can be used for various applications, such as copilots, chatbots, and other content creation.

However, generative AI and LLMs also present significant challenges for cloud providers, who must provide the infrastructure and software to support these workloads. These technologies require massive amounts of computing power, storage, and network bandwidth, as well as specialized hardware and software to optimize performance and efficiency.

Infrastructure Challenges and Solutions

For example, LLM training involves many GPU servers working together, communicating constantly among themselves and with storage systems. This results in east-west and north-south traffic in data centers, which requires high-performance networks for fast and efficient communication.

Similarly, generative AI inference with larger models needs multiple GPUs working together to process a single query. Cloud providers also need to ensure that their infrastructure is secure, reliable, and scalable, as they serve multiple customers with different needs and expectations. Cloud providers must also comply with industry standards and best practices and provide support and maintenance for their services.

The NVIDIA Cloud Partner reference architecture addresses these challenges by providing a comprehensive, full-stack hardware and software solution for cloud providers to offer AI services and workflows for various use cases. Based on NVIDIA's years of experience in designing and building large-scale deployments both internally and for customers, this reference architecture includes:

• GPU servers from NVIDIA and its manufacturing partners, featuring NVIDIA’s latest GPU architectures, such as Hopper and Blackwell, which deliver unparalleled compute power and performance for AI workloads.
• Storage offerings from certified partners, which provide high-performance storage optimized for AI and LLM workloads. These offerings include those tested and validated for NVIDIA DGX SuperPOD and NVIDIA DGX Cloud, proven to be reliable, efficient, and scalable.
• NVIDIA Quantum-2 InfiniBand and Spectrum-X Ethernet networking, which provide high-performance east-west network communication for fast and efficient communication between GPU servers.
• NVIDIA BlueField-3 DPUs, which deliver high-performance north-south network connectivity and enable data storage acceleration, elastic GPU computing, and zero-trust security.
• In/out-of-band management solutions from NVIDIA and management partners, which provide tools and services for provisioning, monitoring, and managing AI data center infrastructure.
• NVIDIA AI Enterprise software, including:
  • NVIDIA Base Command Manager Essentials, which helps cloud providers provision and manage their servers.
  • NVIDIA NeMo framework, which helps cloud providers train and fine-tune generative AI models.
  • NVIDIA NIM, a set of easy-to-use microservices designed to accelerate the deployment of generative AI across enterprises.
  • NVIDIA Riva, for speech services.
  • NVIDIA RAPIDS accelerator for Spark, to accelerate Spark workloads.

Key Benefits of NVIDIA's Reference Architecture

The NVIDIA Cloud Partner reference architecture offers the following key benefits to cloud providers:

• Build, Train and Go: NVIDIA infrastructure specialists use the architecture to physically install and provision the cluster for faster rollouts for cloud providers.
• Speed: By incorporating the expertise and best practices of NVIDIA and partner vendors, the architecture can help cloud providers accelerate the deployment of AI solutions and gain a competitive edge in the market.
• High Performance: The architecture is tuned and benchmarked with industry-standard benchmarks, ensuring optimal performance for AI workloads.
• Scalability: The architecture is designed for cloud-native environments, facilitating the development of scalable AI systems that offer flexibility and can seamlessly expand to meet increasing end-user demand.
• Interoperability: The architecture ensures compatibility among various components, making integration and communication between components seamless.
• Maintenance and Support: NVIDIA Cloud Partners have access to NVIDIA subject-matter experts, who can help address any unexpected challenges that may arise during and after deployment.

The NVIDIA Cloud Partner reference architecture provides a proven blueprint for cloud providers to build and manage high-performance, scalable infrastructure for AI data.