CUDA allocate memory in __device__ function

Question

Is there a way in CUDA to allocate memory dynamically in device-side functions ? I could not find any examples of doing this.

From the CUDA C Programming manual:

Answer 1

According to http://developer.download.nvidia.com/compute/cuda/3_2_prod/toolkit/docs/CUDA_C_Programming_Guide.pdf you should be able to use malloc() and free() in a device function.

Page 122

B.15 Dynamic Global Memory Allocation void* malloc(size_t size); void free(void* ptr); allocate and free memory dynamically from a fixed-size heap in global memory.

The example given in the manual.

__global__ void mallocTest()
{
    char* ptr = (char*)malloc(123);
    printf(“Thread %d got pointer: %p\n”, threadIdx.x, ptr);
    free(ptr);
}

void main()
{
    // Set a heap size of 128 megabytes. Note that this must
    // be done before any kernel is launched.
    cudaThreadSetLimit(cudaLimitMallocHeapSize, 128*1024*1024);
    mallocTest<<<1, 5>>>();
    cudaThreadSynchronize();
}

You need the compiler paramter -arch=sm_20 and a card that supports >2x architecture.