public cloud compute  gpu

Cloud servers specially designed for processing massively parallel tasks

GPU instances integrate NVIDIA Tesla V100 graphic processors to meet the requirements of massively parallel processing. Since they are integrated into the OVHcloud solution, you get the advantages of on-demand resources and hourly billing. These cloud servers are adapted to the needs of machine learning and deep learning.

Powered by NVIDIA Tesla V100

These GPUs are among the most powerful on the market, and are designed for use in datacentres. They accelerate computing in the fields of artificial intelligence (AI) and graphic computing.

NVIDIA GPU Cloud

To provide the best user experience, OVH and NVIDIA have partnered up to offer a best-in-class GPU-accelerated platform, for deep learning and high-performance computing and ​artificial intelligence (AI). It is the simplest way to deploy and maintain GPU-accelerated containers, via a full catalogue. Find out more.

Between one and four cards with guaranteed performance

Tesla cards are delivered directly to the instance via PCI Passthrough, without a virtualisation layer, so that all of their power is dedicated to your use. Up to four cards can be connected to combine their performance. As a result, the hardware delivers all of its computing power to your application.

NVIDIA Tesla V100 Features

Performance with NVIDIA GPU Boost

Bidirectional connection bandwidth

CoWoS Stacked HBM2 memory
  • double-precision, 7 teraFLOPS
  • single-precision, 14 teraFLOPS
  • deep learning, 112 teraFLOPS
  • PCIe 32GB/s
  • capacity, 16GB HBM2
  • bandwidth, 900GB/s

 

Use cases

Image recognition

Extracting data from images to classify them, identify an element or build richer documents is necessary in many industries. With frameworks like Caffe2 combined with the Tesla V100 GPU, medical imaging, social networks, public protection and security become easily accessible.

Situation analysis

Real-time analysis is required in some cases, where an appropriate reaction is expected to face varied and unpredictable situations. This kind of technology is used for self-driving cars and internet network traffic analysis, for example. This is where deep learning comes in, to form neural networks that learn independently through a training stage.

Human interaction

In the past, people learned to communicate with machines. We are now in an era where machines are learning to communicate with people. Whether through speech recognition or the emotion recognition through sound and video, tools such as TensorFlow push the boundaries of these interactions, opening up a multitude of new uses.

Need to train your artificial intelligence with GPUs?

With our AI Training solution, you can train your AI models efficiently and easily, and optimise your GPU computing resources.

Focus on your business instead of the infrastructure that supports it. Launch your training tasks via a command line, and pay for the resources used by the minute.

Get started with OVHcloud AI Training

Usage

1

Get started

Launch your instance by choosing a T1 model and NGC image for your project.

2

Configure

$ docker pull nvcr.io/nvidia/tensorflow
$ nvidia-docker run nvidia/tensorflow t1

3

Use

Your AI framework is ready for processing.

Ready to get started?

Create an account and launch your services in minutes

Pricing Public Cloud

GPU billing

GPU instances are billed like all of our other instances, on a pay-as-you-go basis at the end of each month. The price depends on the size of the instance you have booted, and the duration of its use.