Join the discussion
Write your take first — we'll ask for email only when you're ready to publish.
- Hacker News
- Just make more RAM.by varispeed
- 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.
by rldjbpin - 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.
by DiabloD3 - 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.by physicsguy
- by camel-cdr
- All these AI do is eat hot chip and lieby nozzlegear
- 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.
by einpoklum - 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.
by LogTrim