oh great. More chasing to do. Anyone interested in working on the CUDA integration for Go (https://gorgonia.org/cu)? PRs welcome, as I am quite short on time.
CUDA 11.0
31–40 of 67 posts
Re: CUDA 11.0
#32Does anyone understand why such minor upgrades resulted in a major version bump? Is this some sort of stability check point? Or some other versioning convention?
Well, I think a new microarchitecture means a major bump. So between that and version bumps to to actual major software features, you get to 11 within 13 years or so.
Also, GCC 9.x compatibility may seem minor to some, but is significant for others. I also think there's some C++17 support in kernels - that's something too.
Re: CUDA 11.0
#33Interesting that Fedora support seems to have been dropped. Anyone know why that might be? Edit: oh wait I think I see. Latest supported gcc for CUDA 11 is gcc 9.x, but I think latest Fedora is on gcc 10.
You just have to compile that specific supported version of gcc. On an earlier CUDA, I had to compile gcc-4.9. Unlike Debian, Fedora just seems to remove all traces of old packages.
Re: CUDA 11.0
#34Everytime I have to deal with multiple versions of CUDA on Linux I feel like poking my eyes out. I get that supporting developer libraries that have to interact with hardware is hard but come on...
For something this popular it shouldn't be so hard. I don't think being related to hardware is an excuse. CUDA is not a driver and exists entirely in userspace.
This is the kind of thing that happens when you're dealing with a monopoly.
Re: CUDA 11.0
#35Everytime I have to deal with multiple versions of CUDA on Linux I feel like poking my eyes out. I get that supporting developer libraries that have to interact with hardware is hard but come on...
For something this popular it shouldn't be so hard. I don't think being related to hardware is an excuse. CUDA is not a driver and exists entirely in userspace. This is the kind of thing that happens when you're dealing with a monopoly.
Yes - I would think drivers are even harder from an engineering point of view but as far as I know they have fairly good backwards compatibility for games. I think this is likely because people would be much more reluctant to buy new graphics cards if they broke their older games.
Re: CUDA 11.0
#36Earlier quoted context omitted.
Usually for an API it indicates a breaking change. In this case the removal of some functions which might require refactoring on the consumers end.
And to keep users on a hardware upgrade treadmill.
Do you mean removing Pascal support deprecating Maxwell? How long you'd need it to be supported to be satisfied?
Even with OSS projects discussions about ending support are not easy.
Re: CUDA 11.0
#37Earlier quoted context omitted.
I have to use containers with nvidia-docker because NVIDIA so consistently and relentlessly breaks things without so much as a glance at backward compatibility.
The annoying thing is that nvidia-docker is still not great. You still have to deal with the driver installed outside the container, and it makes a big difference. Furthermore it seems like even the CUDA runtime is typically not installed in the container, but rather injected in by the nvidia-docker container runtime. It is not fun to deal with.
You don't have to use nvidia-docker to use cuda with docker. I made my own cuda containers based on Debian and pass the devices to the docker run command. I mount the libcuda and libnvidia libraries as volumes. I think that's what you mean by injecting the runtime.
Here's an example Dockerfile: https://github.com/dmm/docker-debian-cuda/blob/master/Docker...
And here's an example docker run command:
docker run -it --rm $(ls /dev/nvidia* | xargs -I{} echo '--device={}') $(ls /usr/lib/x86_64-linux-gnu/{libcuda,libnvidia}* | xargs -I{} echo '-v {}:{}:ro') dmattli/debian-cuda:10.0-buster-debug /bin/bash
Verbose but it works fine. You still have to have the nvidia driver installed on the host system.
Re: CUDA 11.0
#38Everytime I have to deal with multiple versions of CUDA on Linux I feel like poking my eyes out. I get that supporting developer libraries that have to interact with hardware is hard but come on...
The most frustrating part is the gcc version dependency.
Re: CUDA 11.0
#39I'd like to play with CUDA, but I just got a new laptop without an Nvidia GPU, coming from one that had a built in Nvidia GPU. It's got a thunderbolt port, but unfortunately most of the gpu's are quite expensive at around 400$. Does anyone know any cheaper options?
Re: CUDA 11.0
#40Does anyone understand why such minor upgrades resulted in a major version bump? Is this some sort of stability check point? Or some other versioning convention?
It supports a whole new architecture (Ampere) and all the good stuff that comes with it: Multi-Instance GPU partitioning, new number formats (Tfloat32, sparse INT8), 3rd gen of Tensor Cores, and asynchronous copy/asynchronous barriers. These are huge features.