Category Archives: GPUBox Artist

Major update is coming…


As we have announced a while ago, within the next update of GPUBox Arion will join the portfolio of officially supported GPU-based renderers. Our cooperation with RandomControl developers already resulted in exceeding the limit of 8 GPUs (that some of you might have noticed while watching our previous video). We are thrilled about that because the GPUBox-Arion combination exhibits astonishing potential in terms of scalability and performance. Just take a look at the video:

Stay tuned for the next updates. Soon we are going to reveal some more information about supported scientific applications and further GPU-based renderers (yes, V-Ray RT as well…)

GPUBox is going to support Arion


We can now officially announce that GPUBox is going to support RandomControl Arion.

Arion is a hybrid, GPU-accelerated, and physically-based production render engine capable of generating hyper-real images. RandomControl offers it in stand-alone version as well as plugins for 3ds Max and Rhinoceros. First tests of this renderer running on GPUBox proved that it exhibits great scalability and nearly-native performance while using multiple GPUs virtualized with GPUBox.

We launched the Arion benchmark on 4 x GTX 690 (8 GPUs) running within our local testing environment as well as on 6xGRID K520 within GPUBox Web Service:


Official support for this outstanding renderer will be introduced to GPUBox within the next major update. Besides Arion, GPUBox is also going to open for scientific applications such as LAMMPS, CUDASW++, HOOMD-blue, Gromacs or BarraCUDA to name just a few. And last but not least – GPUBox GPUServer will no longer require Linux. Windows version is currently in the beta-tests stage.

Short video tutorials for OServer and GPUServer

Some of our users claimed that the installation process of GPUBox components – especially OServer and GPUServer – is sometimes a bit problematic. As we understand that for lots of GPUBox users it is something completely new, we have prepared two short video tutorials presenting an exemplary installation of OServer and then GPUServer. We believe that those videos will be a good supplement for the documentation. In the video we used the demo version that can be downloaded for free in the Products section of our website. However the installation process for the full version looks nearly the same. Continue reading

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

Next steps of Renegatt Software


The time has come to reveal some of our future plans.

So, let us make it brief and official – Renegatt Software is going to introduce:

Dedicated versions of GPUBox Artist

GPUBox Artist licenses restricted only to a particular application will be available to be purchased at a lower price. At the beginning, we will release GPUBox Artist separately for Blender and Octane. Each version will cost €59 per GPU.

GPUBox Web Service

Thanks to GPUBox Web Service you will be a few clicks away from using more GPUs than ever. The first edition of GPUBox Web Service is going to use Amazon EC2 instances.

Windows Server and Mac OS X Client

At the moment the GPUs can be served to the infrastructure only from Linux servers. Some of you would like to virtualize GPUs under Windows, and this is what we are going to do. Also, we are planning to develop GPUBox Client for Mac OS X.

Support for new applications

More CUDA-based renderers are going to join Blender and Octane.


If you want to be always up-to-date with us, follow Renegatt Software on Twitter/Facebook or subscribe to our newsletter.

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

Performance and scalability in Octane Render


One of the most popular questions regarding GPUBox Artist refers to performance and scalability. We prepared a short but substantial clip that presents you those two aspects of using Octane Render within the GPUBox-powered infrastructure.

For the purpose of this video we used Octane Render 1.55 Standalone running on CentOS 6.4. The scene that was used for the test was well-known OctaneBenchmark scene on default settings (except samples, which were set to 6000) and Path Tracing kernel.

In the first part of the video we compared two rendering sequences. The left side presents rendering the scene on native 4 GPUs (2 x GeForce GTX 690). Simultaneously, on the right side of the screen you can see rendering the very same scene on the same settings, on identical GPUs, but mounted in a different PC and virtualized with GPUBox Artist.

Native rendering was finished after 4:05, while rendering using the GPUs remotely with GPUBox took 4:07.

In the second part we virtualized and engaged another six GeForce GTX 690 cards (12 GPUs) and launched again the same scene on a total number of 16 GPUs comparing it to native rendering on 4 GPUs. Theoretically, rendering on 4 times as much GPUs should result in 4 times faster rendering and this is what happened here – the rendering took 1 minute and 1 second.

During the test we were using a 20Gb/s InfiniBand network, but additionally we launched the same scene on 1 Gb Ethernet which is not presented in the video. The results are shown in the following table: Continue reading

GPUBox Artist Beta is released!


We are proud to announce that the first product using the GPUBox technology is finally released! GPUBox Artist is tailored especially for 3D graphics industry and it enables to share multiple GPU devices between many users simultaneously. And by “multiple” we do not mean a few – we mean dozens! Continue reading

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