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CUDA Toolkit Release Notes
- sergiomattei 7y agoFrom the notes: > CUDA 10.2 (Toolkit and NVIDIA driver) is the last release to support macOS for developing and running CUDA applications. Support for macOS will not be available starting with the next release of CUDA.
- joshklein 7y agoBetween this and the challenges around OpenMP (now generally solved), setting up a Linux workstation just for experimenting was easier than getting it working on my “pro” Apple hardware.
- fortran77 7y agoThis makes sense. Macs don't support their hardware. Researchers and scientists who need CUDA get platforms with the power and capability to support them.
- wlesieutre 7y agoNot surprising given Apple’s apparent vendetta against Nvidia hardware
- snuxoll 7y agoA well deserved vendetta, Nvidia has screwed Apple over multiple times going back to the PowerPC days. After the defective chipset fiasco one can’t blame them for cutting ties.
- arvinsim 7y agoIn the end, it's the customers who lose
- mantap 7y agoIn the end it's apple who loses. Customers can use Linux or Windows, but how is apple going to sell $6000 workstations and $5000 displays without even the option to install aftermarket nvidia cards? OK so Apple doesn't trust nvidia as a supplier but why do they forbid the release of drivers? Total insanity.
- QuixoticQuibit 7y agoThat seems like a very one-sided take considering Apple’s history. Moreover, the reason is almost certainly related to Apple not wanting to proliferate Nvidia’s tools and instead force developers to use their Metal API. AFAIK Apple’s even abandoned OpenCL on macOS.
- sbuk 7y agoSo, you are aguing that NVidia constantly messing up when Apple have used them in good faith as a supplier, followed by the subsequent denial of problems even existing by NVIdia and their refusal to accept any culpability (see Bumpgate), is "a very one-sided take" and eschew it in the belief that this is all about pushing Metal? That seems like the very narrowly held view to me. Perhaps they are thinking the way you propose, but since NVidia hasn't figured anywhere in any of Apple's hardware since Bumpgate, I'd suggest that NVidia being a bad partner has considerably more to do with it.
- benologist 7y agoNearly a decade has passed since nVidia messed up one generation of laptops so probably it's time to let it go. Grudges don't really help anyone, and Apple's so far from innocent they shouldn't promote grudges as solutions to problems, especially as alternatives to consumer-friendly hardware support. In much more recent times Apple themselves ruined four generations of laptops and were deceptive and dishonest about it, until they grudgingly rolled out their free keyboard replacement program which starts expiring for their earliest victims at the end of next year. Apple chose to experiment for 3 additional years at, in aggregate, major expense and inconvenience to their customers. nVidia was never as bad as Apple and it's hypocritical too. How many Foxconn employees killed themselves without Apple permanently prohibiting working with Foxconn? How many child workers have they found in their supply chain without terminating their relationship with suppliers? nVidia obviously solved their one issue, and went on to ship millions of chips in laptops since then without problem.
- deleted 7y ago[deleted]
- vkaku 7y agoSounds like AMD and Intel should sever their ties too.
- mrpippy 7y agoMakes sense, given that the underlying drivers only support macOS 10.13 (which is likely considered out-of-support by Apple now)
- choonway 7y agomac users can always use AMD's openCL offerings...
- StuffedParrot 7y agoI was under the impression OpenCL was deprecated for Mac OS.
- WrtCdEvrydy 7y agoI thought it was still supported and the AMD version of tensorflow was supported as well...
- mrpippy 7y agoYep, deprecated in 10.14 in favor of Metal. I expect it to be like OpenGL, where the existing functionality will stay around in maintenance mode for years to come but never improved. https://developer.apple.com/library/archive/documentation/Performance/Conceptual/OpenCL_MacProgGuide/Introduction/Introduction.html https://developer.apple.com/library/archive/documentation/Pe...
- alphagrep12345 7y agoWhy 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.
- bitL 7y agoNVidia didn't want to pay for failing NVidia chips in MacBooks when they had problems with their manufacturing over half a decade ago and since then Apple tries everything to make NVidia's and its customers' life difficult.
- amelius 7y agoWeren't these chips failing because of bad thermal design of the enclosure?
- mciancia 7y agoThey were failing in any computer with that chip (Nvidia 8600m), whether it was MacBook, Thinkpad or some Dell.
- mikhailt 7y agoNope. This was a confirmed defective GPUs by Nvidia themselves. All companies that used these GPUs were affected. They even sued Nvidia. Here is example: https://blog.dell.com/en-us/nvidia-gpu-update-nvidia-class-action-lawsuit-and-limited-warranty-enhancement/ https://blog.dell.com/en-us/nvidia-gpu-update-nvidia-class-a...
- Symmetry 7y agoNVidia changed solders without changing to a thermal potting compound with the same expansion coefficient as the new solder. Cycles of thermal stress caused the solder to fracture and the chip to lose electrical contact with the board eventually.
- sdan 7y agoTensorflow stopped supporting MacOS w/GPUs a year or two ago. Maybe if you're using Pytorch or some other framework that supports MacOS w/GPU/external gpu... but to my knowledge that doesn't exist/isn't widely used.
- Rebelgecko 7y agoI guess that means we won't be getting a new Webdriver for their graphics cards either :/
- shmerl 7y agoThey are worth each other. Lock-in should be avoided, both from Apple and Nvidia.
- dang 7y agoSubmitted 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 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 kind of thing, as sometimes happens with corporate press releases, then the original title would be misleading and it would arguably be right to change it. But that seems unlikely here? Edit: I suppose we could switch the URL to an article like https://gizmodo.com/apple-and-nvidia-are-over-1840015246 https://gizmodo.com/apple-and-nvidia-are-over-1840015246 if this really is the only story here.
- andybak 7y agoAny 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")
- pilooch 7y agoAs an ML + open source developer for over 10y, MacOS support for deep learning is already long gone, Linux is the prime AI/ML OS. However, Apple and NVidia parting away is a good omen for GPU competition I believe. Whatever Apple hw comes up with, if usable outside MacOS software stack, it'd be an interesting alternative.
- suyash 7y agoWe need a CUDA alternative for non NVIDIA gpu's, specially on a Mac.
- nevi-me 7y agoWould this from AMD count? https://rocm.github.io/ https://rocm.github.io/
- PeterisP 7y agoIt's not supported on Mac, and even on Linux seems to have weird limitations on specific kernel versions. It also supports just a subset of AMD chips, which doesn't seem to include the actual AMD chips of the different Macs that I have available. ROCm would count if it's mature enough so that the setup "just works" on any reasonable environment (in the way that it mostly is so for the major ML platforms on nvidia/CUDA) but it does not yet seem ready for that.
- nevi-me 7y agoYou make a good point, I forgot that it's not Mac or Windows compatible, and the limited hardware support.
- Athas 7y agoOpenCL 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.
- fulafel 7y agoDeprecated by Apple in regards native OS X support for OpenCL, important distinction.
- ActorNightly 7y agoI dont really understand this, why would you use a Mac for anything compute intensive?
- mister_hn 7y agoFully 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
- bayindirh 7y agoIn my understanding, Radeon Instinct cards are not doing that bad. Yes, they're not supported by CUDA, but they're not slouching either.
- solidasparagus 7y agoIt's extremely hard to use the standard ML toolchains for GPU on anything that doesn't support CUDA.
- ComodoHacker 7y ago>standard ML toolchains So Nvidia has achieved their goal and pushed ATI out of ML market?
- fluffy87 7y agoATI was never in the AI market. They have been trying, but their efforts are a joke compared tobest their competition is doing.
- JosephRedfern 7y agoIt'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).
- bayindirh 7y agoThanks 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.
- 7y ago
- netheril96 7y agoSo nvcc is completely based on clang now?
- Athas 7y agoIt has been for a long time. Only the very earliest versions of CUDA had an nvcc based on Open64.
- xvilka 7y agoThis is why CUDA and NVIDIA are a cancer. Such an important piece of infrastructure for both graphics and ML should be open source.
- llukas 7y agoYou surely can write one yourself or pay for development. If that doesn't work maybe you could help developing one of the existing packages?
- Athas 7y agoThe corresponding AMD infrastructure and most related tools are fully open source. The driver is even upstreamed in the Linux kernel!
- fluffy87 7y agoThose tools suck.
- esistgut 7y agoI am a full stack web developer using a Linux environment as my development environment. I plan to start learning some ML related stuff and I just recently bought a Radeon 5700 XT, the current high end consumer GPU from AMD. Before this I had an RX 580. The driver support on Linux is fine but not optimal, there are multiple issues regarding color ranges, dual monitor support and with Navi based hardware (5700/5700XT) plain hardware freezes/hangs. I did not personally experience the hangs but I installed the 5.4-rc8 kernel and compiled mesa 20 from the git just to avoid them in the first place. There is no Navi support on ROCm and the prefered way to have OpenCL on older hardware like Polaris (RX 580 for example) is to just extract the relevant files from the closed source driver. I still prefer something with open source drivers but AMD is far behind NVIDIA in terms of GPGPU software support, I cant't honestly understand what their strategy is and why they are allowing the majority of developers to tie themself and their careers to NVIDIA.
- pjmlp 7y agoNot at all, Khronos just keeps missing the boat that there is a large community that doesn't want to be stuck with C for GPGPU programming. When they took steps to embrace other languages the boat was already in high sea.
- amelius 7y agoI'm using CUDA under Ubuntu, and have noticed that the CUDA library uninstalls itself every so often. Has anyone else experienced this?
- ktm5j 7y agoYou probably installed a kernel update and the nvidia kernel module didn't recompile itself. You can avoid having to reinstall the whole driver package by just running "dkms autoinstall" and then "modprobe nvidia" You may first need to unload any loaded nvidia modules (built for an older kernel).. So some combination of "rmmod nvidia_modeset" "rmmod nvidia_uvm" "rmmod nvidia_drm" "rmmod nvidia" and then run dkms I run a ~1000 node server room for a computer science graduate program at a university.. keeping these drivers built and loaded properly has been a nightmare! Nvidia really needs to get things worked out if they want to keep pushing the GPGPU stuff
- mroche 7y agoWhat distro are you running in your labs? At my university’s cluster running with RHEL 6 (same applies to RHEL 7, hopefully they managed the upgrade over the summer) all that’s needed is installing dkms, then the CUDA repo from NVIDIA, which includes the driver and CUDA packages. Any kernel update will rebuild the kmod on reboot. I’m not 100% certain if that repo is Tesla cards only (which is what we were) but ELRepo also has the generic driver and associated bits (same as negativo, but those are very granular). DKMS is really the only piece that’s necessary to keep the system running (other than keeping an eye on which kernel version the kmods were based on if using the non-NVIDIA repo). DKMS also works just fine with the NVIDIA provides installer, just make sure you have the libglvnd bits installed before you install the driver.
- proverbialbunny 7y agoThere is an nvidia dev apt repo that is great for installing and setting CUDA up because apt does all the heavy lifting for you. I've never had any problems with it. First an optional prerequisite, for updated video drivers: ``` sudo apt-get install -y software-properties-common && sudo add-apt-repository -y ppa:graphics-drivers/ppa && sudo apt-get update && sudo apt-get install -y nvidia-driver-NNN ``` (Eg, nvidia-driver-435) This is sometimes a required prerequisite, because these drivers have 32bit and 64bit binaries in them where the ones from nvidia's website or normal apt packages only have the 64bit drivers. (Eg, it's a requirement for Steam and many video games, which will suddenly stop working when CUDA is installed.) Then there is CUDA itself: ``` sudo apt-get install -y gnupg2 curl ca-certificates && curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub https://developer.download.nvidia.com/compute/cuda/repos/ubu... | sudo apt-key add - && sudo echo "deb https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 https://developer.download.nvidia.com/compute/machine-learni... /" > /etc/apt/sources.list.d/nvidia-ml.list && sudo apt-get update && sudo apt-get install -y nvidia-cuda-toolkit libcudnn7 libcudnn7-dev ``` (If also using cudnn.) Also note: NVIDIA currently doesn't officially support Ubuntu 19, but their 18.04 repo works perfectly for 19. In the future you can always try grabbing from https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1904/x86_64/ https://developer.download.nvidia.com/compute/cuda/repos/ubu... instead.
- throwawaysea 7y agoSo what do people here use to learn/fool around with GPU-dependent ML stuff (non production use cases)? A non Mac laptop? Or do you do it all in the cloud? Using the cloud presumably gets expensive over time and I also would think that the overhead of dealing with a cloud setup and all the associated legwork to get started can be frustrating compared to working locally.
- proverbialbunny 7y agoIf you're learning the basics, a laptop is great, because you're not number crunching for days at a time. If you're doing anything process intensive, gpu or cpu, you'll want a desktop or cloud. Sure, some laptops are fast, but they head up, so there isn't much of a way around it.
- Vomzor 7y agoA mac to ssh into my linux desktop. It’s cheaper to buy your own gpu.
- charlescearl 7y agoHas anyone experimented with ClojureCL [1]? It claims to run on MacOS. [1] https://clojurecl.uncomplicate.org/articles/getting_started.html https://clojurecl.uncomplicate.org/articles/getting_started....
- naveen99 7y agoI couldn't find any documentation on libcu++ i guess i'll have to download the new sdk, and see if there are samples or look at the headers.