Can someone give a clear explanation of how the new and delete keywords would behave if called from __device__ or __global__ code in CUDA 4.2?

Where does the memory get allocated, if its on the device is it local or global?

It terms of context of the problem I am trying to create neural networks on the GPU, I want a linked representation (Like a linked list, but each neuron stores a linked list of connections that hold weights, and pointers to the other neurons), I know I could allocate using cudaMalloc before the kernel launch but I want the kernel to control how and when the networks are created.

Thanks!

1 Answer

C++ new and delete operate on device heap memory. The device allows for a portion of the global (i.e. on-board) memory to be allocated in this fashion. new and delete work in a similar fashion to device malloc and free.

You can adjust the amount of device global memory available for the heap using a runtime API call.

You may also be interested in the C++ new/delete sample code.

CC 2.0 or greater is required for these capabilities.

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