Setting up arivis Pro

arivis Pro has been built from the ground up for the visualization and processing of very large datasets while being RAM independent. This, consequently, has a significant effect on how the software is implemented and affects how we deal with the most common bottlenecks in computing.

arivis Pro is a program for Windows 64-bit operating systems. There is no MacOS or Linux version. Please have a look at this article for more information on Installing arivis Pro on Apple hardware. The minimum requirement for support is Windows 10, but Windows 11 is also supported. The software may work partially on earlier versions, but note that these are not supported configurations.

Also, while the low memory requirements of arivis Pro make it theoretically capable of processing large datasets in 32-bit environments, the high cost of maintenance of two separate builds of the software and the relative scarcity of 32-bit systems means we no longer offer a 32-bit version. 

So, which hardware configuration should you choose?

The computer you already have, as long as it runs Windows 10 or better, has 100GB or more of free hard disk space, and has a dedicated GPU that supports OpenGL 4.3 will probably be fine for most image analysis tasks and visualization. But if you want to buy a new machine dedicated to arivis Pro then the following recommendations are useful guidelines.

Also, please see this article Choosing the right license type for recommendations regarding licensing options.

For detailed descriptions of the process of activating, updating or transferring licenses is covered, see this article.

• If you use ML and have a compatible GPU you should install this and use it
• The installation is normally part of the standard installation process
• If you've already installed the software, or you're installing it on an offline workstation, you can download and install this package independently using the instructions below 

With the release of Vision4D 3.6, arivis added the ability to use Deep Learning (DL) inference for segmentation of images. This can significantly improve the accuracy of segmentation of complex structures in a range of applications and images.

To optimize the DL operations we use the ONNX runtime libraries. These can be used with both GPU and CPU, but using the GPU to run these operations can dramatically improve the speed of processing. However, the GPU libraries are quite large (600MB) and only compatible with NVIDIA GPUs. Since not all users will require this, either because they have no need for DL or no compatible GPU, we do not include the GPU package as part of the Vision4D installation files and instead download it on request during the installation process. 

Once the GPU packages have been installed, the option to use the GPU for ML acceleration will appear in the application preferences:

Note that this option may remain greyed out if the GPU drivers that are currently installed are not compatible. In that case, the user should update the drivers and restart the system. Once this option is enabled the software will default to using the GPU for any ML operation.

This package makes use of CUDA, a proprietary technology available on NVIDIA GPUs. Please see this Wikipedia article or consult the NVIDIA documentation to find out if your GPU is supported. 

If you have a dedicated GPU. make sure you go into the graphics driver preferences and configure it to use the GPU by default for any arivis application.

• Win 7-8:
• Right-click on the desktop and open the graphics card control panel. Select Manage 3D Settings from the tasks on the left, then select the Program Settings tab. Click the Add button and browse to your arivis installation. Then select the option to use the high performance GPU.
• Win 10 and above:
• Go to the Start menu and open the Settings app. Go to the System settings and then to Display. Scroll down the panel to find the Graphics settings link. Click the Browse button and navigate to your arivis installation, then select your dedicated GPU.

Note that this needs to be done for all arivis installations on your device, so if you are using arivis Pro and arivis Pro VR you will need to configure both.

If you need to preserve battery life, maybe because you are doing image analysis on the go then sacrificing graphics performance for the duration of the session may be an acceptable compromise, but you may also choose to run the application with the dedicated GPU on other occasions. You can specify which GPU to use on launching the application by right-clicking on the application icon and choosing the Run with graphics processor option:

You can then choose with GPU to use as needed and the application will launch.

But it is also possible to permanently set a preference for wich GPU to use that that the application will automatically select a specific GPU on launch unless specified otherwise as above.

Virtual machines are a convenient way to create environments for software utilization that are unmoored from physical hardware and can be easily reset, copied, or transferred to new machines. However, these same abilities affect several aspects of how the software is licensed and operated.

arivis software products are protected from unauthorized use by a licensing system provided by a third-party provider. This licensing system allows institutions who purchase licenses to protect their asset, and us as software vendors from the illegal distribution of our products. Licensing works by locking the software to a specific piece of hardware, typically a computer or dongle.

In the case of a hard key, the license is effectively located on a USB dongle, and whichever machine has the key plugged in is able to read the license and make it available to users. 

In the case of soft licenses, the key is activated on a computer by making a digital fingerprint of the machine on which it is activated and locking the activation to this fingerprint.

This is important when using a virtual machine. If you have a dongle, the dongle must be visible to the virtual machine. If you are using a soft key, changes to the virtual machine, such as copying it to a new computer, will change the VM's fingerprint and irreversibly invalidate the license. Therefore, if you activate a soft license on a VM, you MUST deactivate the license prior to making any changes to the VM and reactivate once the changes are completed. Failure to do this will invalidate the license and support related to License invalidation due to VM changes are not covered by warranty or maintenance and may be chargeable.

Please see the article Activating, updating and transferring licenses to find out more about activating and transferring licenses.

VMs are, of course, very handy in a range of scenarios. Indeed, the arivis development team does use VMs extensively for testing in-house for these very reasons. However, users should be aware of the distinct differences in how VMs operate to ensure that they have a great user experience. arivis is keen to support users in whatever environment they find most useful to them, and making users aware of the consequences of running in such an environment is part of what the support team can do to ensure a great user experience. 

The arivis support team will always try to help users if they are experiencing issues linked to VMs, but you should be aware that our ability to support will be limited by your configuration, and issues caused by user error may not be covered by maintenance agreements and may therefore be chargeable.

Generally, it is best to use Vision4D on a system that is local to the data storage. Since data storage of very large datasets can be challenging on standard desktop or laptop systems a common workaround is to use a high-end imaging workstation with lots of storage, and to access this workstation using Remote Desktop Protocol (RDP).  However, these configurations have historically been problematic with regard to GPU utilization. This article aims to clarify some of those issues and provide solutions.

Good graphics cards are essential for good 3D rendering performance. Our system hardware recommendation article goes into more details on this topic, but for now, we'll keep it simple and say that Vision4D needs at least OpenGL 4.3 support or higher to display data in the 4D viewer. 

RDP allows users to remotely access the computing resources of a machine other than the one they are physically in contact with. However, using RDP is in many ways significantly different from directly accessing the machine. One of these differences is how the graphics card uses its resources. Historically, using GPUs over RDP has required professional cards with specific drivers, and this is still a good guideline as server cards are generally tuned for multiple concurrent usage and use with RDP. Gaming cards, which are usually significantly cheaper, have historically not provided good support for use with RDP. However, recent driver updates from NVIDIA have significantly improved the compatibility of their GPUs with RDP. 

The following configurations have been tested internally and confirmed to work:

These systems have been tested using access from a variety of clients, including Mac and Linux clients.

The use of Vision4D over RDP is also limited by the licensing system we use.

As of 2020, soft licenses are delivered with RDP enabled by default.

Licenses purchased earlier may be upgraded to enable RDP under certain circumstances. If you have a soft license but RDP is disabled, please contact support using the link at the top of this page.

If you have a Network license, hard or soft, RDP is on by default.

If you have a hard local license, these licenses can only be configured for RDP for arivis Vision4D 3.4 or above. Older versions of Vision4D do not support RDP with a hard local key. If RDP is necessary, please contact your local sales representative to discuss replacing your hard key for a soft key or any other options that might work for you.

While the configurations tested above work, remote desktop GPU support is mostly outside of arivis' control. However, there are a few things we recommend:

1. Always make sure you have the most up to date windows version and drivers for your graphics card.
2. If your GPU doesn't work over RDP, first check that it works when used locally and then contact your IT support team or your GPU manufacturer.
3. Pro graphics card are generally recommended for server installations and multi-user setups.