Including stuff like Fortran, Haskell, Java, .NET via PTX, Python JIT, IDE tooling integration with major IDEs, graphical GPU debugging and profiling, libraries and co?
> In fact, contrary to the competition, one can play with CUDA even on laptops, go figure.
This is the part people don't get. You can program cuda anywhere on any Nvidia card, unlike other companies' chips you don't need a data center gpu to have full programmability. It's been this way for over a decade
We haven’t yet released support for tcgen05, but we’ll deal with it the same way we deal with other inline PTX: parsing it and converting it to target-appropriate instructions together with the rest of the program.
This is something we’ve done already for the hopper-class tensorcore instructions, and the blackwell ones will map similarly, though likely with a kernel launch involved.
A guess would be some time next year — since our public launch our focus has generally been on API coverage and increasingly recently, on performance.
While performance improvements will always remain a target, we're soon at full coverage of the core CUDA APIs and will be shifting an increasing amount of effort towards developer tooling.
Then I guess all the best.