Only one command
$ gpubox add 20 /enter
to get 20 GPU devices ready to use in less than a second

What is GPUBox?

A cutting-edge technology bringing the GPU to cloud computing


Present and future applications of GPUBox

Key advantages

What can you gain by deploying GPUBox on your infrastructure?

What is GPUBox?

GPUBox is a virtualization technology and a cloud-ready GPU-computing platform that provides a completely new angle on the usage of the GPUs. It is the foundation of a fully-functioning, scalable and elastic cloud infrastructure.

The GPUBox software simplifies GPU management by separating the application and operating systems from the underlying GPU devices. It is a solution that allows the dynamic sharing of GPU devices from the same pool, by many users. The GPU-cloud-enabled infrastructure can be set up, regardless of its size and purpose, by small 3D graphics studios as well as larger providers. Also, the GPUBox infrastructure can be extremely efficient thanks to recent network technology with its high throughput and low latencies.

GPUBox enables on-demand provisioning of GPU devices to a physical or virtual machine with a Linux or Windows operating system. The pool of GPU devices is shared among users which leads to reduction in the total power consumption and idle-running hardware.

Basic usage of the GPUBox software is easy to understand. For example, to allocate 20 GPU from the pool of devices to the Client, the user issues a simple command in the terminal:

$ gpubox add 20

After that, the supported applications will recognize 20 GPUs as if they were installed in the system. When the GPUs are no longer needed, the user can easily remove them from the system by using the command:

$ gpubox drop all

With GPUBox, the GPU cloud infrastructure is not limited only to the most expensive professional devices. GTX-class cards can be easily applied.

GPUBox Artist Introduction and User Scenarios
PDF | 2.97 MB | Download


The first implementation of the GPUBox technology is GPUBox. It responds to the needs of today's 3D graphics purposes by leveraging CUDA-based renderers with GPU cloud computing.

The next implementation of GPUBox will be GPUBox Scientist, crafted especially for applications that might be used for such computations as:

  • molecular and fluid dynamics
  • bioinformatics
  • computational chemistry
  • numerical analytics
  • structural mechanics
  • computational finance
  • weather and climate simulations
  • materials science
  • seismic simulations

Key advantages

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