Live data from Hacker News

CUDA Toolkit Release Notes

docs.nvidia.com

41–50 of 126 posts

Re: CUDA Toolkit Release Notes

#41

Why doesn't apple support NVIDIA though? Considering the whole ML and AI community use only NVIDIA GPUs, it sucks that we can't use apple laptops for the same.

Why would you do anything compute intensive on laptops that suffer from cooling issues?

Why make such a broad statement at all? There are laptops for nearly every need - yes there are some which will throttle very quickly and are only good for light work, but there are laptops in every size that have decent enough cooling that they can run at max load 24/7 without any issues. As to why someone would do this - can you really not think of a single reason?

Re: CUDA Toolkit Release Notes

#42
post #22

We need a CUDA alternative for non NVIDIA gpu's, specially on a Mac.

AIUI, Vulkan can be used for compute - so why not do that? It might work reasonably well on both nVidia and non-nVidia hardware. Of course, this requires GPU-enabled software to implement Vulkan support, but that's one-time work.

Last year, I supervised a student project that involved writing a Vulkan backend for a compiler that already possessed CUDA and OpenCL backends. While I recall that everything ended up working, it didn't run all that fast. The vast majority of the problems were related to the language used for encoding the shaders, SPIR-V.

Among the difficulties we encountered, I recall the need to use an offline optimiser to do trivial things like CSE and constant folding. CUDA and OpenCL will do this during kernel compilation, but Vulkan implementations seems to be designed as non-optimising (in order for loading to be faster, I assume). This is a perfectly understandable design, but it means it's a little more awkward to use. For direct programming (as compared to a compilation target), it's a lot more awkward.

Another issue was that basic Vulkan is very restricted, as I assume it's supposed to be usable on simple hardware. Additional functionality can be enabled through a collection of extensions. One particular problem I recall is that our code generator assumes the existence of general pointers, for example such that the same memory can be used for different types of values at different times. SPIR-V has/had a very strict notion of pointers, and no way to cast between different types without an extension, and that extension was IIRC not implemented by NVIDIA or AMD. There were lots of these kinds of issues.

In the end, Vulkan is usable for compute - after all, a single master's student (admittedly one who's very bright) managed to implement a Vulkan-targeting compiler backend in half a year. However, at the time I concluded that it's not as mature or as practical as CUDA or OpenCL, for reasons that seem perfectly solvable. However, for direct programming, the SPIR-V that is needed for shaders is completely inaccessible. It would be like writing machine code (not assembly) by hand. I assume graphics programmers have some layer on top to provide a sane interface, but since we were writing a compiler anyway, it wasn't a big deal for us.

Re: CUDA Toolkit Release Notes

#43
post #19

Submitted title was "Nvidia drops support for CUDA on macOS". We changed that for a while to "CUDA 10.2 is the last release to support macOS", which is language from the article itself. Since then someone emailed and asked why the title was like that in light of the discussion at https://news.ycombinator.com/item?id=21617016 , so I've reverted to the article's title. Edit: If the article were more a burying the lede…

Any title that gives us a clue why the story is worthy of note. At the moment it's frustrating as you have to click through to find out if you want to click through.

(title at the time of my comment was "CUDA Toolkit Release Notes")

Re: CUDA Toolkit Release Notes

#44
post #32

This is why CUDA and NVIDIA are a cancer. Such an important piece of infrastructure for both graphics and ML should be open source.

The corresponding AMD infrastructure and most related tools are fully open source. The driver is even upstreamed in the Linux kernel!

Re: CUDA Toolkit Release Notes

#45
post #19

Submitted title was "Nvidia drops support for CUDA on macOS". We changed that for a while to "CUDA 10.2 is the last release to support macOS", which is language from the article itself. Since then someone emailed and asked why the title was like that in light of the discussion at https://news.ycombinator.com/item?id=21617016 , so I've reverted to the article's title. Edit: If the article were more a burying the lede…

Why is the threshold for changing urls and titles lowering all the time?

It seems like it has went from something rare, only used in very clearcut cases to something you use daily.

Re: CUDA Toolkit Release Notes

#46
post #27
post #22

We need a CUDA alternative for non NVIDIA gpu's, specially on a Mac.

OpenCL is decent, and although it's deprecated, it's probably going to continue working for years. It's not as nice as CUDA for direct programming, but don't most people access CUDA through higher-level libraries anyway? You probably would not be able to tell whether those use OpenCL or CUDA behind the scenes.

Deprecated by Apple in regards native OS X support for OpenCL, important distinction.

Re: CUDA Toolkit Release Notes

#47

Fully understandable..anyways none is doing ML on Apple hardware due to ATi Chipsets.. last Apple HW with Nvidia graphic cards are old or running Linux or Windows with Bootcamp anyways

In my understanding, Radeon Instinct cards are not doing that bad. Yes, they're not supported by CUDA, but they're not slouching either.

It's extremely hard to use the standard ML toolchains for GPU on anything that doesn't support CUDA.

Re: CUDA Toolkit Release Notes

#48

Fully understandable..anyways none is doing ML on Apple hardware due to ATi Chipsets.. last Apple HW with Nvidia graphic cards are old or running Linux or Windows with Bootcamp anyways

In my understanding, Radeon Instinct cards are not doing that bad. Yes, they're not supported by CUDA, but they're not slouching either.

It's one thing to have an API and hardware support for such things, it's a different thing entirely to have support from the major ML stacks (pytorch/tensorflow etc).

Re: CUDA Toolkit Release Notes

#49

Fully understandable..anyways none is doing ML on Apple hardware due to ATi Chipsets.. last Apple HW with Nvidia graphic cards are old or running Linux or Windows with Bootcamp anyways

In my understanding, Radeon Instinct cards are not doing that bad. Yes, they're not supported by CUDA, but they're not slouching either.

Thanks for all the replies. I'm not very knowledgeable about the current state of the big ML frameworks' status. I know better now. Thanks again.

Re: CUDA Toolkit Release Notes

#50
post #45
post #19

Submitted title was "Nvidia drops support for CUDA on macOS". We changed that for a while to "CUDA 10.2 is the last release to support macOS", which is language from the article itself. Since then someone emailed and asked why the title was like that in light of the discussion at https://news.ycombinator.com/item?id=21617016 , so I've reverted to the article's title. Edit: If the article were more a burying the lede…

Why is the threshold for changing urls and titles lowering all the time? It seems like it has went from something rare, only used in very clearcut cases to something you use daily.

It's based on what dang likes or not and the propaganda he wants to spread. Anything that makes his favorite companies or political ideology look bad is changed
Post reply on HN