Democratizing AI with NVIDIA AI Enterprise

Table of Contents

1. Introduction
2. The Challenge of Implementing AI
3. NVIDIA AI Enterprise Platform
4. Hardware and Software Stack for AI
5. NVIDIA Certified Servers
6. Container Orchestration Platforms
7. NVIDIA AI Tools, Frameworks, and Applications
8. Support and Maintenance
9. NVIDIA AI Enterprise and HPE Esmeral
10. HPE GreenLake
11. Conclusion

NVIDIA AI Enterprise Platform: Democratizing AI for All Companies

Artificial intelligence (AI) is one of the hottest topics in enterprise tech today. However, many companies are still hesitant to implement AI due to the complexity of the technology. NVIDIA, the world's leading AI solutions provider, has taken up the challenge of democratizing AI for all companies across all industries with their NVIDIA AI Enterprise platform.

The Challenge of Implementing AI

Implementing AI requires a hardware and software stack that can handle the demands of AI workloads. This includes capable hardware, a container platform, and a load of AI software. While it is possible to design, configure, and install all of these components by yourself, it requires a lot of knowledge, testing, trial and error, resources, time, and money. Even then, you cannot be sure you've chosen the best route to success. Additionally, when there's a problem, you have dozens of support phone numbers to call, and no one takes overall comprehensive responsibility for the stack.

NVIDIA AI Enterprise Platform

NVIDIA AI Enterprise is a comprehensive AI platform that simplifies the implementation of AI workloads. It provides a complete hardware and software stack that is pre-configured and bundled for You to hit the ground running. NVIDIA AI Enterprise supports both on-premises and public cloud deployments.

Hardware and Software Stack for AI

To run AI workloads, you need capable hardware. NVIDIA AI Enterprise provides a list of NVIDIA certified servers that are tested and qualified by NVIDIA to run even the most demanding AI workloads. If you prefer to use public cloud, NVIDIA has recommendations about suitable services from all major hyperscalers too.

Next, you will want to use a sophisticated container orchestration platform. At the moment, NVIDIA AI Enterprise supports Red Hat OpenShift via Vertanzu and different flavors of Kubernetes. Support for more container platforms is regularly added.

For the software bit, NVIDIA has a broad selection of AI tools, frameworks, and applications that NVIDIA has bundled and pre-configured for you to hit the ground running. For instance, there's multi-instance GPUs that allow for sharing one physical GPU with multiple containers, virtual machines, and users. For data preparation, there's NVIDIA Rapids. For training, NVIDIA TAU Toolkit, PyTorch, and TensorFlow. For inferencing, TensorRT. And to deploy your AI project at Scale, NVIDIA Triton Inference Server.

NVIDIA Certified Servers

NVIDIA certified servers are tested and qualified by NVIDIA to run even the most demanding AI workloads. These servers are designed to deliver the highest performance and reliability for AI workloads. NVIDIA certified servers are available from leading server manufacturers such as Dell, HPE, Lenovo, and Supermicro.

Container Orchestration Platforms

NVIDIA AI Enterprise supports Red Hat OpenShift via Vertanzu and different flavors of Kubernetes. These container orchestration platforms provide a flexible and scalable environment for running AI workloads. They allow you to manage and orchestrate containers across multiple hosts, and provide features such as load balancing, automatic scaling, and self-healing.

NVIDIA AI Tools, Frameworks, and Applications

NVIDIA AI Enterprise provides a broad selection of AI tools, frameworks, and applications that NVIDIA has bundled and pre-configured for you to hit the ground running. These tools include multi-instance GPUs, NVIDIA Rapids, NVIDIA TAU Toolkit, PyTorch, TensorFlow, TensorRT, and NVIDIA Triton Inference Server. NVIDIA AI Enterprise also supports other popular AI frameworks such as MXNet, Caffe, and ONNX.

Support and Maintenance

NVIDIA AI Enterprise provides one single support phone number to call in case of an issue. This is a huge AdVantage, especially with as complex environments as AI. NVIDIA takes overall comprehensive responsibility for the stack, so you don't have to worry about calling dozens of support phone numbers.

NVIDIA AI Enterprise and HPE Esmeral

Together with HPE Esmeral, NVIDIA AI Enterprise can provide a complete and holistic AI solution from hardware to production lifecycle management. HPE Esmeral provides a complete software platform for AI, machine learning, and analytics. It includes a container platform, data Fabric, and AI lifecycle management. NVIDIA AI Enterprise provides the hardware and AI software stack. Together, they provide a complete and holistic AI solution.

HPE GreenLake

If you want to take this to the next level, you can get all of the above - HPE Esmeral, NVIDIA AI Enterprise, and all the hardware - via HPE GreenLake. In this case, you will get everything as a service. Hardware will be owned by HPE, and all installations, configurations, scaling, and maintenance will be taken care of by HPE, NVIDIA, and their partner networks. All you have to do is focus on using the AI environment and pay only for what you use.

Conclusion

NVIDIA AI Enterprise is a comprehensive AI platform that simplifies the implementation of AI workloads. It provides a complete hardware and software stack that is pre-configured and bundled for you to hit the ground running. NVIDIA AI Enterprise supports both on-premises and public cloud deployments. Together with HPE Esmeral, NVIDIA AI Enterprise can provide a complete and holistic AI solution from hardware to production lifecycle management. If you want to take this to the next level, you can get all of the above via HPE GreenLake.