Using our setup wizard and pre-built Docker Images you can deploy the GPU Instance within 60 seconds. The pre-built images also allow you to deploy an Instance including CUDA support, PyTorch and Jupyterlab during this time.
Every GPUaaS Instance features dedicated resources. For example GPU or CPU computing time is not shared between users. You get maximum performance without any queues.
Instances are hosted in our own infrastructure. We use our own edge data centers in renewable energy plants in several regions. The servers are located in Germany and therefore under EU data protection.
Without prior knowledge of our frontend or even Docker, it is possible to deploy an AI instance in just 60 seconds.
Watch the video to see how easy and fast the deployment is with our four-step setup wizard.
GPU as a Service has never been easier.
Our decentralized and 100% green infrastructure uses no additional virtualization other than Docker. No virtual hardware like vCPUs. Just dedicated CPU cores (each with two threads), RAM, SSD and of course GPUs.
This allows us to achieve maximum performance, agility and simplicity. Exactly what other large providers can no longer provide.
ExaMesh Instances: Cheap, simple, super fast and environmentally friendly.
Already in 2019, we were the first provider to run HPC Instances with 100% green energy. We don’t just use co2 certificates to do this. All of our servers run inside green power plants.
Here you can see how we install the V100 Instances in one of our wind turbines.
Whenever and no matter what the request. We are there for you.
Accounts can be used by multiple members of your team and manage any number of Instances and SSH keys.
Management of each Instance is always possible via SSH and your command line.
Nobody knows the exact location of your Instance. Our infrastructure is decentralized.
