Hi, David. It’s possible to target PTX using: -fsycl-targets=nvptx64-nvidia-cuda-sycldevice and in my experience, things work rather well; it’s also a good way to measure the performance of *real* data transfers, i.e. not using Intel UMA. Note that certain things don’t yet work, e.g. experimental::printf() and mkl::rng, so you’ll need to workaround such limitations. Vince

On Jul 16, 2020, at 12:20 PM, David Poole via Ecp-aurora-sdk-discuss <[email protected]> wrote:

Hi all,

My team and I have been working on porting our codebase from CUDA to DPC++, via construction of a mini-app. This process has been going rather well when it comes to running on the Iris Gen9 GPU. However, I have also had an interest in getting the ported DPC++ code to run on NVIDIA GPUs.

What I am wondering is, is it possible to run SYCL/DPC++ code on NVIDIA GPUs at the moment? Based on my experiments and the contents of https://software.intel.com/content/www/us/en/develop/articles/intel-oneapi-d..., my suspicion is that it is not yet; but I may be wrong about that. And if it is currently possible to run SYCL/DPC++ code on NVIDIA GPUs, how would one go about that?

Thank you very much in advance!

Sincerely, -David Poole

----------------------------------------------- "It is the mark of an educated mind to be able to entertain a thought without accepting it." - Aristotle

David Poole Iowa State University 201 Spedding Hall [email protected]

"I would rather have questions that can't be answered than answers that can't be questioned." - Richard Feynman

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