Comes from Quansight/open-gpu-server#31
@wolfv and @baszalmstra asked in today's core call about the possibility of using the recently added Cirun + self-hosted GHA runner infra to add beefy Windows runners for the most demanding feedstocks. I think the idea is to sponsor this for PyTorch packages, in principle.
From the top of my head, this is what needs to happen, roughly:
- Choose a Cirun-compatible cloud provider for the Windows runners.
- Create VM images for Windows containing the necessary bits (compilers and other tooling not present by default). Make sure the licensing aspects are ok.
- Configure the cloud provider accordingly, and register the credentials in the Cirun app for conda-forge.
- Add support for registration and access control in the admin-requests + .cirun infra.
- Optional. Figure out the legal bits for liabilities and service abuse (e.g. restrict to approved users or maintainers).
Comes from Quansight/open-gpu-server#31
@wolfv and @baszalmstra asked in today's core call about the possibility of using the recently added Cirun + self-hosted GHA runner infra to add beefy Windows runners for the most demanding feedstocks. I think the idea is to sponsor this for PyTorch packages, in principle.
From the top of my head, this is what needs to happen, roughly: