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NVIDIA DGX Cloud

NVIDIA DGX Cloud

  • Fully Managed AI Platform: Access to NVIDIA’s high-performance AI infrastructure without the need for on-premises hardware.

  • Advanced GPU Clusters: Each instance includes 8 NVIDIA H100 or A100 80GB Tensor Core GPUs, totaling 640GB of GPU memory, suitable for training large-scale AI models.

  • High-Speed Networking: Utilizes NVIDIA NVLink and NVSwitch technologies for high-bandwidth, low-latency interconnects between GPUs, enhancing multi-node training performance.

  • Optimized Storage Solutions: Equipped with high-performance NVMe storage to support demanding AI workloads.

  • DGX Cloud Create: A Kubernetes-based platform for orchestrating AI workloads, facilitating efficient training and fine-tuning of models.

  • Serverless Inference: Deploy AI models with automatic scaling and efficient GPU utilization, eliminating the need for managing underlying infrastructure.

  • Benchmarking Tools: Provides templates and guidelines for evaluating model performance, supporting scalability up to 2,048 GPUs.

  • Multi-Cloud Support: Available through major cloud providers like Oracle Cloud Infrastructure, Microsoft Azure, Google Cloud, and Amazon Web Services, offering flexibility and global scalability.

  • Expert Support: Direct collaboration with NVIDIA engineers to optimize model performance and deployment strategies.

  • Predictable Pricing: Transparent monthly pricing starting at $36,999 per instance, inclusive of hardware, software, storage, and 24/7 support.

Diagram illustrating NVIDIA DGX Cloud's unified AI platform, showcasing layers for AI development, deployment, and scalable GPU infrastructure across multi-cloud environments.
Visual representation of NVIDIA DGX Cloud architecture, highlighting integrated tools for AI model training, serverless inference, and seamless scalability on leading cloud platforms.

NVIDIA DGX Cloud: A Unified Cloud Platform for AI Development and Deployment

Overview

NVIDIA DGX Cloud is a comprehensive cloud platform developed by NVIDIA, designed to enable organizations to access advanced computational power for AI training and inference without the need for complex on-premises infrastructure.

Technical Specifications

  • Graphics Processing Units (GPUs): Each DGX Cloud instance includes 8 NVIDIA H100 or A100 80GB Tensor Core GPUs, providing a total of 640 GB of GPU memory.
  • Networking and Connectivity: Utilizes NVIDIA NVLink and NVSwitch technologies to deliver high-bandwidth inter-GPU communication, combined with RDMA networking to minimize latency and maximize data transfer speeds.
  • Storage: Equipped with high-performance NVMe storage optimized for demanding AI workloads.

Infrastructure Components of DGX Cloud

  • Management Software: NVIDIA’s Base Command Platform is employed to orchestrate and monitor AI training workloads efficiently.
  • High-Performance Networking: DGX Cloud leverages low-latency, high-bandwidth networking to enable seamless scalability for distributed AI tasks.

Key Features and Services

  • DGX Cloud Create: A Kubernetes-based AI workload orchestration platform that facilitates training and fine-tuning of models. This fully managed service includes both a user-friendly graphical interface and command-line tools for interacting with GPU clusters.
  • Serverless Inference: Enables scalable and efficient deployment of AI models without the need to manage infrastructure, leveraging automatic GPU resource optimization.
  • Benchmarking Capabilities: Offers ready-to-use templates and guidelines to benchmark AI models such as Llama 3.1, Grok1, and NeMo Megatron at scale, supporting configurations up to 2,048 GPUs.

Collaborations with Cloud Service Providers

NVIDIA DGX Cloud is integrated with leading cloud service providers including Oracle Cloud Infrastructure (OCI), Microsoft Azure, Google Cloud, and Amazon Web Services (AWS), offering global-scale access to high-performance computing resources.

Use Cases and Clients

  • Amgen: Utilizes DGX Cloud in conjunction with the BioNeMo software suite to accelerate biologics drug discovery.
  • Cerence: Trains automotive-specific large language models to enhance in-vehicle user experiences.
  • ServiceNow: Develops intelligent virtual assistants and customer service agents using DGX Cloud infrastructure.
  • Deloitte: Employs DGX Cloud and NVIDIA BioNeMo to advance large language models in pharmaceutical research and drug development.

Key Advantages

  • Access to NVIDIA Expertise: Clients benefit from direct collaboration with NVIDIA engineers to optimize model performance and deployment.
  • Multi-Cloud Support: DGX Cloud is available across various cloud platforms, including Oracle Cloud Infrastructure, Microsoft Azure, and Google Cloud, offering flexibility and resilience.

Pricing

Each DGX Cloud instance, equipped with 8 GPUs and 640 GB of GPU memory, starts at $36,999 per month. This pricing includes hardware, software, storage, and 24/7 expert support.

Conclusion

NVIDIA DGX Cloud provides a robust end-to-end solution for organizations aiming to accelerate and scale their AI initiatives.

With state-of-the-art infrastructure, cutting-edge software platforms, and specialized support, DGX Cloud empowers enterprises to fast-track AI innovation across industries.

NVIDIA DGX Cloud

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Technical walkthrough on how to get started with NVIDIA Quantum-X800.

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NVIDIA Silicon Photonics Resources

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World’s First End-to-End 800Gb/s Networking

The NVIDIA Quantum-X800 platform is the next generation of NVIDIA Quantum InfiniBand, purpose-built for trillion-parameter-scale AI models and comprised of the NVIDIA Quantum-X800 InfiniBand switch, NVIDIA ConnectX®-8 SuperNIC, and LinkX cables and transceivers.

The new platform supports advanced hardware-based, In-Network Computing with Scalable Hierarchical Aggregate Reduction Protocol (SHARP)™ v4, adaptive routing, and telemetry-based congestion control, enabling a new frontier of AI innovation.

The NVIDIA Quantum-X800 InfiniBand switch provides 144 ports of 800Gb/s connectivity per port. It includes hardware-based In-Network Computing with SHARP v4, adaptive routing, telemetry-based congestion control, performance isolation capabilities, and a dedicated port supporting the Unified Fabric Manager (UFM). NVIDIA Quantum-X800 switches also add advanced power-efficiency features, including low-power link state and power profiling.

The NVIDIA Quantum-X800 switch provides increased performance and power efficiency to significantly reduce scientific computing, AI workload completion time, and energy costs.

Quantum-X silicon photonics switches further reduce total power consumption and latency by minimizing the distance and number of connections between optics and electronics.

 

NVIDIA ConnectX-8 SuperNIC

The NVIDIA ConnectX-8 SuperNIC delivers 800Gb/s connectivity with ultra-low latency and supports the latest in advanced In-Network Computing. Based on the ConnectX architecture, it continues to provide accelerated MPI hardware engines, quality of service, adaptive routing, congestion control, and more.

The NVIDIA Quantum-X800 platform connectivity options with the NVIDIA LinkX® interconnect portfolio provide the maximum flexibility for building a preferred network topology, using connectorized transceivers with passive fiber cables and linear active copper cables (LACCs).

 

Description

NVIDIA DGX Cloud: A Unified Cloud Platform for AI Development and Deployment

Overview

NVIDIA DGX Cloud is a comprehensive cloud platform developed by NVIDIA, designed to enable organizations to access advanced computational power for AI training and inference without the need for complex on-premises infrastructure.

Technical Specifications

  • Graphics Processing Units (GPUs):
    Each DGX Cloud instance includes 8 NVIDIA H100 or A100 80GB Tensor Core GPUs, providing a total of 640 GB of GPU memory.
  • Networking and Connectivity:
    Utilizes NVIDIA NVLink and NVSwitch technologies to deliver high-bandwidth inter-GPU communication, combined with RDMA networking to minimize latency and maximize data transfer speeds.
  • Storage:
    Equipped with high-performance NVMe storage optimized for demanding AI workloads.

Infrastructure Components of DGX Cloud

  • Management Software:
    NVIDIA’s Base Command Platform is employed to orchestrate and monitor AI training workloads efficiently.
  • High-Performance Networking:
    DGX Cloud leverages low-latency, high-bandwidth networking to enable seamless scalability for distributed AI tasks.

Key Features and Services

  • DGX Cloud Create:
    A Kubernetes-based AI workload orchestration platform that facilitates training and fine-tuning of models. This fully managed service includes both a user-friendly graphical interface and command-line tools for interacting with GPU clusters.
  • Serverless Inference:
    Enables scalable and efficient deployment of AI models without the need to manage infrastructure, leveraging automatic GPU resource optimization.
  • Benchmarking Capabilities:
    Offers ready-to-use templates and guidelines to benchmark AI models such as Llama 3.1, Grok1, and NeMo Megatron at scale, supporting configurations up to 2,048 GPUs.

Collaborations with Cloud Service Providers

NVIDIA DGX Cloud is integrated with leading cloud service providers including Oracle Cloud Infrastructure (OCI), Microsoft Azure, Google Cloud, and Amazon Web Services (AWS), offering global-scale access to high-performance computing resources.

Use Cases and Clients

  • Amgen:
    Utilizes DGX Cloud in conjunction with the BioNeMo software suite to accelerate biologics drug discovery.
  • Cerence:
    Trains automotive-specific large language models to enhance in-vehicle user experiences.
  • ServiceNow:
    Develops intelligent virtual assistants and customer service agents using DGX Cloud infrastructure.
  • Deloitte:
    Employs DGX Cloud and NVIDIA BioNeMo to advance large language models in pharmaceutical research and drug development.

Key Advantages

  • Access to NVIDIA Expertise:
    Clients benefit from direct collaboration with NVIDIA engineers to optimize model performance and deployment.
  • Multi-Cloud Support:
    DGX Cloud is available across various cloud platforms, including Oracle Cloud Infrastructure, Microsoft Azure, and Google Cloud, offering flexibility and resilience.

Pricing

Each DGX Cloud instance, equipped with 8 GPUs and 640 GB of GPU memory, starts at $36,999 per month.
This pricing includes hardware, software, storage, and 24/7 expert support.

Conclusion

NVIDIA DGX Cloud provides a robust end-to-end solution for organizations aiming to accelerate and scale their AI initiatives.

With state-of-the-art infrastructure, cutting-edge software platforms, and specialized support, DGX Cloud empowers enterprises to fast-track AI innovation across industries.

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Diagram illustrating NVIDIA DGX Cloud's unified AI platform, showcasing layers for AI development, deployment, and scalable GPU infrastructure across multi-cloud environments.

NVIDIA DGX Cloud

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