Vultr Launches GPU Stack and Container Registry for AI Model Acceleration Worldwide

Configuring and provisioning GPUs is a notoriously painful activity. To provide some relief, Vultz announced it has launched the Vultr GPU Stack and Container Registry for AI model acceleration worldwide. This stack and registry will help digital startups and enterprises around the globe to build, test, and operate AI models at scale. It will accelerate the development, collaboration, and deployment of machine learning (ML) and AI models. Developer and data science teams can quickly tune and train their models on their own data sets, with everything pre-configured, down to their Jupiter notebooks.

As one of the world’s leading privately-held cloud computing platforms, Vult has over 1.5 million customers across 185 countries. The GPU Stack and Registry is set to be available across Vultr’s 32 cloud data centers in six continents. Vultr has been in the news recently, with its cloud alliance with Yext and the introduction of the Vultr WebApp.

The Vultr Container Registry makes AI pre-trained NVIDIA NGC models available worldwide for on-demand provisioning, training, development, tuning, and inference. The Vultr GPU Stack is designed to support instant provisioning of the full capabilities of NVIDIA GPUs.

According to Dave Salvator, director of accelerator computing graphics of NVIDIA, a key advantage of using Vultr GPU Stack and Container Registry is that it provides organizations with instant access to the entire library of pre-trained LLMs on the NVIDIA NGC catalog. This enables them to accelerate their AI initiatives and provision and scale NVIDIA cloud GPU instances from anywhere.

Contant is the creator and parent company of Vultr. J.J. Kardwell, CEO of Constant, said that “at Vultr we are committed to enabling the innovation ecosystems — from Miami to São Paulo to Tel Aviv, Europe and beyond — giving them instant access to high-performance computing resources to accelerate AI and cloud-native innovation,”.

He further added “By working closely with NVIDIA and our growing ecosystem of technology partners, we are removing barriers to the latest technologies and offering enterprises a composable, full-stack solution for end-to-end AI application lifecycle management. This capability enables data science and engineering teams to build on their global teams’ models without having to worry about security, local compliance, or data sovereignty requirements.”

The development, testing, and deployment of AI and ML models can get extremely complex and this is set to become even more challenging with looming regulations for safe, secure, and transparent development of AI technology. One of the biggest challenges is the configuration and provisioning bottlenecks. The best tools and technologies are needed to build, run, test, and deploy AI and ML models.

Some of these challenges will be addressed with the launch of the Vultr GPU stack. which comes with a full array of NVIDIA GPUs, including NVIDIA cuDNN, NVIDIA CUDA Toolkit, and NVIDIA drivers for instant deployment. The Vultr GPU Stack provides a finely tuned and integrated operating system and software environment to remove the complexity of configuring GPUs, calibrating them to the model requirements, and integrating them with the AI model accelerators.

Data scientists, engineering teams, and developers across the globe can bring models and frameworks for the NVIDIA NGC catalog to get started on their AI model development and training with a click of a button.

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