Media Server 23.3

# GPU Requirements

To accelerate processing by using a GPU, your system must have a NVIDIA graphics card that meets the following requirements.

Media Server Configuration | GPU Requirements
--- | ---
`CUDAVersion=10` | CUDA compute capability version 3.0 to 7.5 (Kepler, Maxwell, Pascal, Volta, or Turing micro-architecture).
`CUDAVersion=11` | CUDA compute capability version 3.5 to 8.6 (late Kepler, Maxwell, Pascal, Volta, Turing, or Ampere micro-architecture).

All Quadro and Tesla series cards that meet this requirement are supported. GeForce GTX series cards that meet this requirement are supported, but only with headless Linux operating systems. Tegra series cards are not supported, but you can request support by contacting OpenText. Media Server has been tested with NVIDIA Quadro K6000, Quadro M6000, and Tesla K80 graphics cards.

The number of concurrent tasks that you can run on the GPU is constrained by the resources (such as the amount of memory) available on the graphics card. To achieve the best performance, the amount of memory in the machine must match or exceed the amount of RAM available on the GPU(s). For example, if you have two GPUs and each has 12 GB RAM, the machine must have at least 24 GB RAM to use the full performance of the GPUs.

If you are installing Media Server on a virtual machine, the virtual machine might need additional configuration to use the GPU successfully.

## Install the NVIDIA CUDA Driver

To use GPU acceleration, you must install the NVIDIA CUDA driver. The following table shows the required driver version.

Platform | Driver version (CUDA 10) | Driver version (CUDA 11)
--- | --- | ---
Windows | 411.31 or later | 452.39 or later
Linux | 410.48 or later | 450.80.02 or later

The driver can be installed independently, or by installing the appropriate version of the CUDA toolkit. OpenText recommends installing the driver only because this is easier and faster, and only installs the required components.

To install the NVIDIA CUDA driver on Windows

- Download the driver from http://www.nvidia.co.uk/Download/index.aspx?lang=en-uk. If asked to choose a "Download Type", select "Production Branch" because this option provides stable, supported drivers. After downloading the driver, run the installation program as an administrator, and follow the on-screen instructions.

To install the NVIDIA CUDA driver on Ubuntu

1. Verify that your machine is running a supported operating system. Run the following command:

       lsb_release -a

   The operating system is described:

       Distributor ID: Ubuntu
       Description:    Ubuntu 14.04.3 LTS
       Release:        14.04
       Codename:       trusty

2. Verify that a CUDA-compatible card is available. Run the following command:

       lspci | grep -i nvidia | grep -i VGA

   This should produce output similar to:

       0f:00.0 VGA compatible controller: NVIDIA Corporation GF106GL [Quadro 2000] (rev a1)
       28:00.0 VGA compatible controller: NVIDIA Corporation GK110GL [Quadro K6000] (rev a1)

   You must verify that one or more of these GPUs support the required CUDA Compute Capability version (see above). In the previous example, the Quadro 2000 GPU is not supported.

3. Install the essential utilities required to install the NVIDIA driver, by running the following command.

       sudo apt-get install build-essential

4. Install the NVIDIA driver by running the following commands. Consult the table, above, for the minimum required driver version.

       sudo apt-get purge nvidia*
       sudo add-apt-repository ppa:graphics-drivers/ppa
       sudo apt-get update
       sudo apt-get install nvidia-410
       sudo reboot

5. Verify that the driver installation was successful by running the `nvidia-smi` command. The driver version must meet the minimum version described above:

       410.48

## Configure the GPU (Windows only)

Perform this step only if you are running Media Server on Windows. This step is not necessary on Linux.

To use a GPU to accelerate Media Server processing tasks, you must place the GPU in TCC mode. In this mode the graphics card is used for computation only and does not provide output for a display. Unless you use TCC mode, the GPU does not provide adequate performance and can be slower than using a CPU. Many GPUs are not in TCC mode by default, so you must place the card in TCC mode using the `nvidia-smi` tool.

Copyright 2023 Open Text
Version 23.3 | Last updated June 2023

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Product: IDOL Media Server 23.3

Topic Title: GPU Requirements