Is there Mac OS support?
CUDA 11.0
41–50 of 67 posts
Re: CUDA 11.0
#42I'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?
If you just want to try for a few hours, you can add GPU(s) onto a GCP CE instance. Along with the trial credits it should get you a few hours poking around with cuda.
Otherwise, get a pre-owned GTX950 (one that doesn't require external power supply) and a TB3 to PCI-E x16 adapter. Not enclousure, adapter. Should cost you around $200 all in IIRC. And it allows you to upgrade the card furthur down the line since most of the cost is the adapter.
Re: CUDA 11.0
#43I'd like to play with CUDA, but I just got a new laptop without an Nvidia GPU, coming from one that had a built in Nvidia GPU. It's got a thunderbolt port, but unfortunately most of the gpu's are quite expensive at around 400$. Does anyone know any cheaper options?
You could get an Nvidia Jetson Nano for $100 USD
https://developer.nvidia.com/embedded/jetson-nano-developer-...
Re: CUDA 11.0
#44I'd like to play with CUDA, but I just got a new laptop without an Nvidia GPU, coming from one that had a built in Nvidia GPU. It's got a thunderbolt port, but unfortunately most of the gpu's are quite expensive at around 400$. Does anyone know any cheaper options?
If you just want to try for a few hours, you can add GPU(s) onto a GCP CE instance. Along with the trial credits it should get you a few hours poking around with cuda. Otherwise, get a pre-owned GTX950 (one that doesn't require external power supply) and a TB3 to PCI-E x16 adapter. Not enclousure, adapter. Should cost you around $200 all in IIRC. And it allows you to upgrade the card furthur down the line since most…
Do you know what exactly I should search for when looking for a "TB3 to PCI-E x16 adapter"? Will this utilize all thunderbolt lanes available? I've got a newer laptop that, I believe, has all lanes available.
Re: CUDA 11.0
#45Everytime 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...
Once I discovered buster-backports nonfree has up-to-date cuda it’s been smooth sailing.
Re: CUDA 11.0
#46Is there Mac OS support?
Nope. That's mostly on Apple though, as they discourage all APIs that aren't Metal.
Re: CUDA 11.0
#47Re: CUDA 11.0
#48Earlier quoted context omitted.
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.
I've got confused for a sec on "removing Pascal support", as some of the 10XX GPUs are only 2 years old. Looks like Pascal stays, and Maxwell is removed indeed (it was deprecated in 10.2).
Re: CUDA 11.0
#49Everytime 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...
I run multiple versions all the time. They install in completely independent locations. What's the issue you're having?
Re: CUDA 11.0
#50Everytime 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.
The economic incentive is simple: open-sourcing the driver will allow an open-source API to interact with the hardware, allowing AMD/other competitors to support the same API. So instead of competing at the silicon level, Nvidia chooses to set up unnecessary barriers to entry at massive cost to developers/users.
Like Torvalds says [1]: Fuck You, Nvidia.