![]() ![]() Run the available GPU Coding Interface examplesÄeactivating the 3rd example and usage of GLEW/GLFW packages NVIDIA CUDA TOOLKIT VISUAL STUDIO HOW TOHow to set up GPU Coding Interface for Linux How to set up GPU Coding Interface for Windows A brief table of contents and which topics you should expect in the "Solution" section: More informations on this in the following "Solution" section. NVIDIA CUDA TOOLKIT VISUAL STUDIO CODENote: Visual Studio Community IDE is required when using Visual Studio Code on Windows. All steps will be explained for the operating systems Windows and Linux independently. If you don't want to use these packages, we will explain how to disable the packages (and consequently example no. GLEW and GLFW packages are only required for the 3rd example. You can also use other versions for GLEW and GLFW, but the CUDA Toolkit has to be greater than or equal to version 11.2. Microsoft Visual Studio IDE (only for Windows - can be Community, Professional or Enterprise) Furthermore you will need the following tools and versions compiled and/or installed on your operating system for this exemplary project: ![]() The required "GPUCodingIF_VSCode_Example.zip" is attached to this FAQ and can be found at the bottom of this page. We are providing a specific GPU Coding Interface configuration solution for Visual Studio Code in this example, which is just the same example folder from the CarMaker installation, but with aready defined paths and a specific. Note that this FAQ focusses on creating a system environment with Visual Studio Code, which is currently the most popular IDE available for free. It is mostly meant for beginners with these tools or such setups. This FAQ shall provide you a basic understanding and act as a quick start guide to get in touch with the GPU Coding Interface and the three existing examples. To create your own signal processing functions and runtime libraries, one has to do several steps beforehand. It allows to provide manufacturer specific signal processing algorithms to customers, suppliers and other users as a binary runtime library to protect their intellectual property. For this purpose, the internal signal processing of CarMaker can be deactivated for each supported RSI and replaced by an own implementation. It was developed to enable any easy integration of custom signal processing models into the CarMaker simulation. We introduced our new GPU Coding Interface feature starting with CarMaker R11, which is an open programmable user interface for the GPU based 'Raw Signal Interfaces (RSIs)'. ![]()
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