notation VS Dagger.jl

Notary v2: The evolution to Notary v2 brought improvements in signature portability and integration with third-party key management solutions. However, it does not provide a certificate authority, leaving public key discovery for open-source image verification as an unresolved issue.

Notation

Notation is another command-line too that lets you digitally sign artifacts. And those signatures essentaily become the stamps of approval for the different things in your software supply chain. For example, container images.

Notary is the CNCF project name and is often referenced when referring to the process of signing digital artifacts, but Notation is the command line tool that does the heavy lifting. Run the following commands to install Notation.

It should be interoperable, that's the goal. I proposed some idea for nv2 here: https://github.com/notaryproject/nv2/issues/39 and here: https://github.com/notaryproject/nv2/issues/40 too.

Firstly, I'll say that we already have work started to implement out-of-core directly in Dagger: https://github.com/JuliaParallel/Dagger.jl/pull/289.

With that PR in place, it should be possible to define a "storage device" which is backed by a database. I haven't had a chance to actually try this, since the PR still needs quite some work and testing, but it's definitely something on my radar!

I'm not sure that's necessarily the domain of a low-level package like CUDA.jl though (which I assume you're referring to). That kind of interface is more the domain of higher-level packages like https://github.com/JuliaParallel/Dagger.jl/ and to a lesser extent https://juliagpu.github.io/KernelAbstractions.jl/stable/. Moreover, the jury is still out on whether the built-in Distributed module is an ideal abstraction for every use-case (clusters, heterogeneous compute, etc.)

WRT Nx, my biggest question is how they'll crack the problem of still needing big balls of C++ and the shims everywhere to get acceleration. Creating a compiler that generates efficient GPU or other accelerator code is a massive research project with no clear winners, never mind the challenge of reconciling the very mutation-heavy needs of GPU compute with a mostly immutable language model.