Cpu speed accelerator new 8.02/24/2023 ![]() ![]() Unless you use TCC mode, the GPU does not provide adequate performance and can be slower than using a CPU. In this mode the graphics card is used for computation only and does not provide output for a display. To use a GPU to accelerate Media Server processing tasks, you must place the GPU in TCC mode. Perform this step only if you are running Media Server on Windows. Verify that your machine is running a supported operating system. To install the NVIDIA CUDA driver on Linux After downloading the driver, run the installation program as an administrator, and follow the on-screen instructions. If asked to choose a "Download Type", select "Optimal Driver for Enterprise" because this option provides stable, supported drivers. To install the NVIDIA CUDA driver on Windows Micro Focus recommends installing the driver only because this is easier and faster, and only installs the required components. This can be installed independently, or by installing the CUDA toolkit version 8.0. ![]() To use GPU acceleration, you must install the NVIDIA CUDA driver: If you install GPU Media Server on Ubuntu, Micro Focus recommends that you install a headless version of Ubuntu server. Install Media Server from the ZIP Package.Install Media Server as described in one of the following sections: If you are installing Media Server on a virtual machine, the virtual machine might need additional configuration to use the GPU successfully. In the configuration file for each Media Server, you must set the GPUDeviceID parameter to specify which GPU to use (set this parameter to a different value for each Media Server). To run several instances of Media Server with GPU support on the same physical machine, the machine must have multiple GPUs. 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. 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). The number and size of concurrent tasks that you can run on the GPU is constrained by the amount of memory available on the graphics card. Media Server has been tested with NVIDIA Quadro K6000, Quadro M6000, and Tesla K80 graphics cards. Tegra series cards are not supported, but you can request support by contacting Micro Focus. GeForce GTX series cards that meet this requirement are supported, but only with headless Linux operating systems. All Quadro and Tesla series cards that meet this requirement are supported. To accelerate processing by using a GPU, your system must have a NVIDIA graphics card with CUDA compute capability version 3.0 to 6.1 (Kepler, Maxwell, and Pascal micro-architecture). Using a GPU rather than the CPU can significantly increase the speed of training and analysis tasks that use Convolutional Neural Networks. Media Server can use a graphics card (GPU) to perform some processing tasks. Open topic with navigation Enable GPU Acceleration ![]()
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