The interesting part is that this is less "CUDA now runs on RISC-V" and more "Nvidia is defining what a CUDA-capable RISC-V server has to look like."
That could end up being a pretty influential de facto server profile for the architecture.
nxobject 10 days ago [-]
Beyond the significant PCI-e requirements, I'm tickled pink that many of the server platform requirements are "do what x86 does"... ACPI, UEFI, a TPM. I hope they do a better job with standards compliance than some of the shadier Wintel OEMs!
classichasclass 10 days ago [-]
And Nvidia is big enough that they could impose some order on the ecosystem that the ecosystem so far has either been unable or unwilling to impose on itself. The wild west of one-offs can continue to make their application-specific designs while everyone else will presumably benefit from a reasonably standardized platform.
einpoklum 10 days ago [-]
CUDA is proprietary technology, guarded by patents and mostly closed-source. And its originator, NVIDIA, while being a member of the Khronos consortium, and technically supporting OpenCL, makes it much more difficult for you to do anything in OpenCL than in CUDA - even though it is sometimes almosy zero effort to enable some OpenCL equivalent (e.g. : Half-precision types. They exist in CUDA; in OpenCL on NVIDIA - you can't have them).
So, live with CUDA on other hardware? No thank you.
CUDA used to target POWER9 architecture but it was so niche that you ended up compiling from source literally everything since no wheels were available for it. EasyBuild and Spack were full of half broken recipes for the magic incantations necessary to build fundamental packages for HPC like TensorFlow, etc.
DiabloD3 9 days ago [-]
Don't really know why this is interesting, CUDA is kind of a niche legacy API that Nvidia has kept on life support a little too long.
Just use Vulkan for compute.
brucehoult 9 days ago [-]
Or Mojo, recently acquired by Qualcomm, and even more recently fully open-sourced under Apache 2 license.
rldjbpin 10 days ago [-]
very ironic but easily explainable. as they sell their own integrated platform now, with server rack partners behaving like graphics cards oems now.
to be able to maximize customized solutions, they would like to own the entire stack which is not already commodified. the cpu remains the only final frontier in this.
there are always side-effects possible, but i wonder if all these efforts can be applied outside of ai ever.
varispeed 10 days ago [-]
Just make more RAM.
djmips 10 days ago [-]
hot chips. hot planet.
Ozzie-D 10 days ago [-]
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goglidesdev 10 days ago [-]
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bizstrategy10 10 days ago [-]
[dead]
Rendered at 03:58:39 GMT+0000 (Coordinated Universal Time) with Vercel.
That could end up being a pretty influential de facto server profile for the architecture.
So, live with CUDA on other hardware? No thank you.
Just use Vulkan for compute.
to be able to maximize customized solutions, they would like to own the entire stack which is not already commodified. the cpu remains the only final frontier in this.
there are always side-effects possible, but i wonder if all these efforts can be applied outside of ai ever.