Guides for creating Intel DPPY packages for conda-forge

• I read the conda-forge documentation and could not find the solution for my problem there.

Issue:

We want to start pushing out our packages dpctl, numba-dppy, dpnp to conda-forge to get make them widely available, and want some tips.

a) All of our packages will need the DPC++ compiler. I think we can handle it in our recipes by installing DPC++ (here is an example of what we currently do for dpctl on Github CI: https://github.com/IntelPython/dpctl/blob/48794f78206389f157ea2e86dbabb46fadbab6e8/.github/workflows/generate-coverage.yaml#L22) or explore using a prebuilt Docker image that has oneAPI preinstalled in our recipe.

Do you anticipate any problems with the usage of DPC++ and oneAPI in general in our recipes?

b) We doubt any of the CI systems that are available to feedstock will have Gen9 GPUs. We can of course build the packages without needing a GPU, but will not be able to test them on a GPU. An option can be to test them on a CPU SYCL device (using OpenCL or Level Zero CPU drivers) like we do in our GitHub Actions CI.

Are you aware of any public CI service supports integrated GPUs?

c) We do not support MacOS. Will that be a problem?

@diptorupd @oleksandr-pavlyk @reazulhoque

[AndresGuzman-Ballen]

@PokhodenkoSA We will be publishing the DPC++ compiler conda packages for 2021.3 release in a few weeks. There are 2021.2 versions that are in a test channel, but in any case it should work just fine by adding the following to the meta.yaml:

requirements: build: - {{ compiler(‘dpcpp’) }}

[beckermr]

It is in the docs iirc. You add a specific line to the conda_build_config.yaml. I forget the syntax offhand.