Category Archives: Blender

One GPUBox to rule all GPUs

You can connect all available GPUs, no matter if they are on Linux or Windows, and force  them to work on single render. Moreover you can use the GPUs on demand on any computer connected to the same network, even more, you can share the GPUs with others.

In the following video we are going to show you how to connect additional GPU to already existing GPUBox infrastructure. For the sake of demonstration we used Amazon EC2 instances however you can use any computers with GPUs. We choose EC2 to show you they are on demand and they are really cheap. If you start instances g2.2xlarge as spot, for a dollar you can have about 15 GRID K520 GPUs with the power of GTX 670 each for entire hour.

We connected Windows to already running 8 instances with Linux. Details of configuration are on the picture which speaks for itself.

Connect GPUBox to 9 GPUs You can find more information in our documentation

… so enjoy the watch

Soon we are going to show you

  • side by side how to install, configure and manage GPUs on two computers,
  • and how to start GPUBox on Amazon EC2 infrastructure with ease,

… and of course you can always share your thougts and write to us

GPUBox 1.6.58 released


We are pleased to announce the fresh release of GPUBox. The new version 1.6.58 supports Linux and the most awaited, GPUBox fully supports Windows with super easy to use Setup Wizard.

Along with the new version for Windows operating system we also released Open GPUBox which allows to use up to 4 GPUs for free for any purposes.

Now it is childishly easy to connect at least two computers, install GPUBox and rule all of the available GPUs. You can even create peer-to-peer alike network of GPUs and share the power among the team’s members.

In the new version we fixed a few bugs and improved the stability and the performance.


Major GPUBox 1.6.58 features:

  • Supports Windows and Linux.
  • Open GPUBox, a free version to use for any purposes.
  • Easy to configure and manage.
  • Supports native InfiniBand
  • Intuitive Web Console
  • Sharing the same device among many users
  • Dynamic provisioning of any number of GPU devices
  • Scalability and flexibility
  • Reduction of total cost and better GPU utilization

Download GPUBox:
Documentation online:


GPUBox Web Service teaser


We have published a brief teaser for the possibilities that will be brought to you with the upcoming GPUBox Web Service.

Lots of things are happening in this short video, but the most important is that we combined 50 GPUs from 50 Amazon EC2 instances (we used the g2.2xlarge instance type) with GPUBox and we used Blender as an exemplary application to show how it works.

GPUBox Web Service automatically configures a multi-GPU cloud computing environment that within a few minutes can be accessed from a regular web browser. In other words, you will be a few clicks away from using an extremely powerful infrastructure to render your scenes. Continue reading

Blender Cycles benchmark on GPUBox Artist


In the previous post we delivered you some information about scalability and performance in Octane Render. Now it is time to take a closer look at Blender and see how the situation looks here. We recorded another video showing rendering widely-used benchmark scene BMW 1M by MikePan, but instead of default settings we applied 8000×4200 resolution and 1000 samples.

When it comes to using multiple GPUs, Blender is rather a long-runner than a sprinter: the heavier is the scene and the longer is the rendering, the better is the scalability. Adding more and more GPUs will not be very efficient if simple, low-quality scene is being rendered. Preparing and distributing the scene to GPUs is not always made up with the performance boost during the rendering itself.  But the magic happens while using multiple virtualized GPUs to render complex scenes on high settings. Continue reading

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