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nVIDIA's CUDA is a popular ecosystem for general-purpose GPU programming. Essentially, in CUDA, you write kernels to be executed on a GPU using a slightly-restricted variant of C++. However, you need to annotate functions which run the the GPU-device-side as __device__. (For constexpr function this can be skipped, but only with a certain compiler flag which shouldn't be relied upon.) Also, any host-side code of the standard C++ library is not usable.
I would like to ask that this span implementation be adapted for use with CUDA. I've done something similar for std::array, although there's a bit of unnecessary boilerplate in my additions there.
The text was updated successfully, but these errors were encountered:
Hi @eyalroz, thanks for your interest in this library.
I'm afraid I have no experience with CUDA and no access to Nvidia hardware, so this is not something I would be able to do myself. However I'd be happy to accept patches for CUDA support (suitably protected by macros of course) if you or someone else would like to add it.
nVIDIA's CUDA is a popular ecosystem for general-purpose GPU programming. Essentially, in CUDA, you write kernels to be executed on a GPU using a slightly-restricted variant of C++. However, you need to annotate functions which run the the GPU-device-side as
__device__
. (Forconstexpr
function this can be skipped, but only with a certain compiler flag which shouldn't be relied upon.) Also, any host-side code of the standard C++ library is not usable.I would like to ask that this span implementation be adapted for use with CUDA. I've done something similar for
std::array
, although there's a bit of unnecessary boilerplate in my additions there.The text was updated successfully, but these errors were encountered: