Build and run instructions for CUDA devices

[rickybalin]

This is a request to add documentation for CUDA devices. For example, it would be great to see:

• Instructions for setting up the Conda environment and a .yaml file for CUDA devices
• Instructions for building DPBench (with support for the SYCL implementations)
• Run instructions to target CUDA devices with the benchmarks
• Which implementations of which benchmarks can we run on CUDA devices (CuPy and numba_cuda are expected, but it would be great to be able to run the SYCL implementations too)

Thanks!

[ZzEeKkAa]

Thank you @rickybalin for the feedback! All the cuda implementations are experimental. It should be as easy to get it work as install of all required packages from the product documentation: https://numba.readthedocs.io/en/stable/cuda/overview.html#requirements

Regarding cuda support in sycl - you need to use sycl build with cuda support. The easiest way is to use nightly build: https://github.com/intel/llvm/releases . Please be couches: if you are using nightly release from outside of conda packages, you must not have dpcpp related packages inside conda environment. It may be tricky, since dpctl, dpnp and numba-dpex requires them. You would need to compile those packages using nightly build and update requirements to ignore dpcpp conda dependencies.