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Gpu compare tool11/15/2023 ![]() Then set its value to the index value (0 for the first one, 1 for the second one, and so on) that represents the GPU device you want to use, and restart the application. To do so, first create this environment variable if it doesn't already exist in your system. To use a different GPU, specify it through the CUDA_VISIBLE_DEVICES system environment variable.To specify a GPU or to disable it, you can set up the CUDA_DEVICE_ORDER and CUDA_VISIBLE_DEVICES system environment variables by doing the following: If there is no GPU available in the TCC driver mode, and the CUDA_DEVICE_ORDER environment is left at the default setting, the fastest GPU (with index 0) will be used, unless specified otherwise. Consequently, it will be listed first (index 0) and will be used to run the tool by default. To number the GPUs based on how they are installed in a machine, modify the CUDA_DEVICE_ORDER environment setting to PCI_BUS_ID.Ī GPU in the Tesla Computer Cluster (TCC) is considered to be faster than a GPU in the default Windows Display Driver Model (WDDM). This means that multiple GPUs in a machine will be numbered from fastest to slowest, starting from 0. In the case of multiple GPUs in a system, two system environment variables determine which GPU will be used: CUDA_DEVICE_ORDER and CUDA_VISIBLE_DEVICES.īy default, the CUDA_DEVICE_ORDER system environment variable is set to FASTEST_FIRST. For spatial analysis, it is recommended that you use two GPUs: one for display and the other for computation. In this case, a warning message will be reported when the tool is run indicating that the display may appear unresponsive. However, if your computer has only one GPU, it will be used both for display and for computation. Before running an analysis tool that uses a GPU, you must update the GPU card drivers to the latest available version on the NVIDIA driver update page. When a GPU card is installed on a machine, it comes with a default driver. It must be 5.2 or higher to be supported by the tool. In the relevant section, locate the specific GPU card and note the compute capability value listed for it. Once you determine the type of NVIDIA GPU card, look up its CUDA compute capability on the NVIDIA help page for CUDA GPUs. All the NVIDIA graphics cards, their driver versions, and other properties are displayed. In the control panel window, go to the Help menu and click System Information.In the context menu, click NVIDIA Control Panel. ![]() Right-click an empty area on your desktop.If an NVIDIA graphics card is listed, review the type of GPU installed on your system using the NVIDIA Control Panel: If no NVIDIA brand graphics card is listed, you cannot access this capability and the tool will use the CPU. The brand names and types of graphics cards are listed there. To check the type of graphics card on a Windows computer, open the Device Manager of your system and expand Display Adaptors. Your system must have an appropriate card installed to access this capability. Currently, only NVIDIA GPUs with CUDA compute capability of version 5.2 or later are supported by the tool. Various solutions are available for GPU processing. The resulting data is sent back, and the software reassembles the individual components into a final complete product. The GPU performs the calculations in parallel for all of the small portions at a faster rate. In those cases, the software divides the processing task into many small portions, which are sent to the GPU for computation. Certain types of operations benefit from this approach. Recently, the processing power of GPUs has been directed to perform general computing tasks.įor tools that are GPU accelerated, the raster processing task is directed to the GPU instead of the central processing unit (CPU). The following tools currently support GPU processing:Ī GPU is a hardware component in a computer with the purpose of accelerating the rendering of graphics in the screen display. This technology takes advantage of the computing power of the graphics card in modern computers to improve the performance of certain operations. ![]() ArcGIS Pro offers enhanced performance with the use of graphics processing unit (GPU) processing for some tools. ![]()
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