runner-images VS taichi

Yeah this is a good option if you'd like something to deploy yourself! You can also build an AMI from GitHub's upstream image definition (https://github.com/actions/runner-images/tree/main/images/ub...) if you'd like it to match what's available in GitHub-hosted Actions.

With Depot, we're moving towards deeper performance optimizations and observability than vanilla GitHub runners - we've integrated the runners with a cache storage cluster for instance, and we're working on deeper integration with the compute platform that we built for distributed container image builds - as well as expanding the types of builds we can process beyond Actions and Docker, for instance.

But different options will be better for different folks, and the `philips-labs` project is good at what it does.

Whoa, there's a lot of stuff in there [1] that gets installed straight from vendors, without pinning content checksums to a value known-good to Github.

I get it, they want to have the latest versions instead of depending on how long Ubuntu (or, worse, Debian) package maintainers take to package stuff into their mainline repositories... but this attack surface is nuts.

[1] https://github.com/actions/runner-images/tree/main/images/ub...

I had a similar experience with ARC (actions-runner-controller).

One of the machines in the fleet failed to sync its clock via NTP. Once a job X got scheduled to it, the runner pod failed authentication due to incorrect clock time, and then the whole ARC system started to behave incorrectly: job X was stuck without runners, until another workflow job Y was created, and then X got run but Y became stuck. There were also other wierd behaviors like this so I eventually rebuilt everything based on VMs and stopped using ARC.

Using VMs also allowed me to support the use of the official runner images [0], which is good for compatibility.

I feel more people would benefit from managed "self-hosted" runners, so I started DimeRun [1] to provide cheaper GHA runners for people who don't have the time/willingness to troubleshoot low-level infra issues.

[0]: https://github.com/actions/runner-images

Reminds me: Still waiting for native ARM support on GitHub Actions https://github.com/actions/runner-images/issues/5631

Used https://github.com/actions/runner-images to get the packages needed for Ubuntu 22.04 As the packer requires a builder, I used "null" builder to set it as localhost ref: https://developer.hashicorp.com/packer/docs/builders/null (It was way difficult to figure it out the 1st time) I had to modify the .pkr.hcl file to pick my provisioners. I could not understand the use of /opt/hostedtoolcache folder (which I did later)

taichi – Productive, portable, and performant GPU programming in Python

ETH Zurich is using it for their physics sim courses, University of Utah is using it for simulations (SIGGRAPH 2022), OPPO (they make smart devices running Android), Kuaishou uses it for liquid and gas simulation on GPUs. Lots of GPU accelerated sim stuff.

https://www.taichi-lang.org/

https://www.researchgate.net/publication/337118128_Taichi_a_...

https://github.com/taichi-dev/taichi

Check our the realease note (https://github.com/taichi-dev/taichi/releases) for more improvements.

I've recently started using Taichi (https://taichi-lang.org/) for numerical codes and the fact it doesn't try to trick you into thinking it's numpy is a nice "feature". ;)

Taichi v1.4.0 is released! See what's new: - Taichi AOT, along with a native Taichi Runtime library: Native applications can now load compiled AOT modules and launch Taichi kernels without a Python interpreter. - Taichi ndarray: An array object that holds contiguous multi-dimensional data to allow easy data exchange with external libraries. - Dynamic index: Use variable indices whenever necessary on all backends without affecting the performance of those matrices with only constant indices. See deprecation and more improvements in the release note.

Oh, then if you're not already tied to any particular VFX software, I might as well recommend Taichi again.

It's an upgrade of a basic version. See changes to the source code here: https://github.com/taichi-dev/taichi/pull/6851