Prerequisites

To get started programming with CUDA, download and install the CUDA Toolkit and developer driver. The toolkit includes nvcc, the NVIDIA CUDA Compiler, and other software necessary to develop CUDA applications. The driver ensures that GPU programs run correctly on CUDA-capable hardware, which you'll also need.

You can confirm that the CUDA Toolkit is correctly installed on your machine by running nvcc --version from a command line. For example, on a Mac OSX machine,

$ nvcc --version nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2009 NVIDIA Corporation Built on Thu_Mar_11_12:08:00_PST_2010 Cuda compilation tools, release 3.0, V0.2.1221

outputs the compiler information. If the previous command was not successful, then the CUDA Toolkit is likely not installed, or the path to nvcc (C:\CUDA\bin on Windows machines, /usr/local/cuda/bin on POSIX OSes) is not part of your PATH environment variable.

Additionally, you'll also need a host compiler which works with nvcc to compile and build CUDA programs. On Windows, this is cl.exe, the Microsoft compiler, which ships with Microsoft Visual Studio. On POSIX OSes, this is gcc or g++. The official CUDA Getting Started Guides can tell you which compiler versions are supported on your particular platform.

To make sure everything is set up correctly, let's compile and run a trivial CUDA program to ensure all the tools work together correctly.

```

include

global void foo() { }

int main() { foo<<<1,1>>>(); printf("CUDA error: %s\n", cudaGetErrorString(cudaGetLastError()));
return 0; } ```

To compile this program, copy it to a file called test.cu and compile it from the command line. For example, on a Mac OSX system, the following should work:

$ nvcc test.cu -o test $ ./test CUDA error: no error

If the program succeeds without error, then let's start coding!