Intel oneAPI 2022.3 release

Here is a code I have been developing: GitHub - CaNS-World/CaNS: A code for fast, massively-parallel direct numerical simulations (DNS) of canonical flows. It supports GPU offloading on NVIDIA hardware.

But it is quite more complex than that in the link above. It does run on many GPUs and may use MPI as backend (in addition to other NVIDIA-specific backends for distributed-memory calculations, like NCCL and NVSHMEM, via the cuDecomp library). Feel free to use it for benchmarking and if you face any issues or need help finding a representative problem, I’m here to help. Otherwise, I am sorry, I also do not have the time to come up with simpler examples for your benchmarks :frowning: .

Thanks to everyone that has replied. We’ve just started developing examples using the Nvidia HPC kit and are using Cuda Fortran. We solve the same problem with gfortran, Intel and Nag on the same hardware. We’ll get back in due course.

Jane and I haven’t found any problems using the C interop features with ifx and the classic Intel C and C++ compilers. In the light of the comments made about the removal of the Classic C and C++ compilers we’ll rewrite our examples to use the new LLVM one.