Difference between global and device functions

Can anyone describe the differences between __global__ and __device__ ?

When should I use __device__, and when to use __global__?.

Solution 1:

Global functions are also called "kernels". It's the functions that you may call from the host side using CUDA kernel call semantics (<<<...>>>).

Device functions can only be called from other device or global functions. __device__ functions cannot be called from host code.

Solution 2:

Differences between __device__ and __global__ functions are:

__device__ functions can be called only from the device, and it is executed only in the device.

__global__ functions can be called from the host, and it is executed in the device.

Therefore, you call __device__ functions from kernels functions, and you don't have to set the kernel settings. You can also "overload" a function, e.g : you can declare void foo(void) and __device__ foo (void), then one is executed on the host and can only be called from a host function. The other is executed on the device and can only be called from a device or kernel function.

You can also visit the following link: http://code.google.com/p/stanford-cs193g-sp2010/wiki/TutorialDeviceFunctions, it was useful for me.

Solution 3:

1. __global__ - Runs on the GPU, called from the CPU or the GPU*. Executed with <<<dim3>>> arguments.
2. __device__ - Runs on the GPU, called from the GPU. Can be used with variabiles too.
3. __host__ - Runs on the CPU, called from the CPU.

*) __global__ functions can be called from other __global__ functions starting
compute capability 3.5.