To start developing an application using CUDA, you will need to set up the development environment for it. There are some prerequisites for setting up a development environment for CUDA. These include the following:

• A CUDA-supported GPU
• An NVIDIA graphics card driver
• A standard C compiler
• A CUDA development kit

How to check for these prerequisites and install them is discussed in the following sub section.

As discussed earlier, CUDA architecture is only supported on NVIDIA GPUs. It is not supported on other GPUs such as AMD and Intel. Almost all GPUs developed by NVIDIA in the last decade support CUDA architecture and can be used to develop and execute CUDA applications. A detailed list of CUDA-supported GPUs can be found on the NVIDIA website: https://developer.nvidia.com/cuda-gpus. If you can find your GPU in this list, you will be able to run CUDA applications on your PC.

If you don't know which GPU is on your PC, then you can find it by following these steps:

• On windows:
  1. In the Start menu, type device manager and press Enter.
  2. In the device manager, expand the display adaptors. There, you will find the name of your NVIDIA GPU.
• On Linux:
  1. Open Terminal.
  2. Run sudo lshw -C video.

This will list information regarding your graphics card, usually including its make and model.

• On macOS:
  1. Go to the Apple Menu | About this Mac | More info.
  2. Select Graphics/Displays under Contents list. There, you will find the name of your NVIDIA GPU.

If you have a CUDA-enabled GPU, then you are good to proceed to the next step.

If you want to communicate with NVIDIA GPU hardware, then you will need a system software for it. NVIDIA provides a device driver to communicate with the GPU hardware. If the NVIDIA graphics card is properly installed, then these drivers are installed automatically with it on your PC. Still, it is good practice to check for driver updates periodically from the NVIDIA website: http://www.nvidia.in/Download/index.aspx?lang=en-in. You can select your graphics card and operating system for driver download from this link.

Whenever you are running a CUDA application, it will need two compilers: one for GPU code and one for CPU code. The compiler for the GPU code will come with an installation of CUDA toolkit, which will be discussed in the next section. You also need to install a standard C compiler for executing CPU code. There are different C compilers based on the operating systems:

• On Windows: For all Microsoft Windows editions, it is recommended to use Microsoft Visual Studio C compiler. It comes with Microsoft Visual Studio and can be downloaded from its official website: https://www.visualstudio.com/downloads/.

The express edition for commercial applications needs to be purchased, but you can use community editions for free in non-commercial applications. For running the CUDA application, install Microsoft Visual Studio with a Microsoft Visual Studio C compiler selected. Different CUDA versions support different Visual Studio editions, so you can refer to the NVIDIA CUDA website for Visual Studio version support.

• On Linux: Mostly, all Linux distributions come with a standard GNU C Complier (GCC), and hence it can be used to compile CPU code for CUDA applications.
• On Mac: On the Mac operating system, you can install a GCC compiler by downloading and installing Xcode for macOS. It is freely available and can be downloaded from Apple's website:

https://developer.apple.com/xcode/

CUDA needs a GPU compiler for compiling GPU code. This compiler comes with a CUDA development toolkit. If you have an NVIDIA GPU with the latest driver update and have installed a standard C compiler for your operating system, you are good to proceed to the final step of installing the CUDA development toolkit. A step-by-step guide for installing the CUDA toolkit is discussed in the next section.