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I'm sorry if this is only tangentially on topic: I was reading the article and got to the part related to installing CUDA drivers. I am currently on the marke

by mastazi 10y ago

I'm sorry if this is only tangentially on topic: I was reading the article and got to the part related to installing CUDA drivers. I am currently on the market for a laptop which will be used for self-learning purposes and I am interested in trying GPU-based ML solutions. In my search for the most cost-effective machine, some of the laptops that I came across are equipped with AMD GPUs and it seems that support for them is not as good as for their Nvidia counterparts: so far I know of Theano and Caffe supporting OpenCL and I know support might come in the future from TensorFlow [1], in addition I saw that there are solutions for Torch [2] although they seem to be developed by single individuals. I was wondering if someone with experience in ML could give me some advice: is the AMD route viable? [1] https://github.com/tensorflow/tensorflow/issues/22 https://github.com/tensorflow/tensorflow/issues/22 [2] https://github.com/torch/torch7/wiki/Cheatsheet#opencl https://github.com/torch/torch7/wiki/Cheatsheet#opencl

p1esk 10y ago
No
jfsantos 10y ago
At the current state of things, AMD is definitely not a viable route, but that might change in the future with the "Boltzmann Initiative" [1]. Performance with OpenCL is not comparable with CUDA on NVIDIA GPUs at the moment, and support is lacking in most deep learning frameworks. [1] http://www.amd.com/en-us/press-releases/Pages/boltzmann-initiative-2015nov16.aspx http://www.amd.com/en-us/press-releases/Pages/boltzmann-init...
- mastazi 10y ago
  Thanks, your statement about performance is very helpful. Basically even if my tech stack supported OpenCL I would still be better of with a CUDA-compatible card.
mastazi 10y ago
Thank you @jfsantos and @p1esk. I'm going for a model equipped with an Nvidia GTX card I guess...
SixSigma 10y ago
We used to have a saying "friends don't make friends run closed software". I guess those days have gone.
- mastazi 10y ago
  I hear you, and I really wish an open alternative became prevalent over CUDA.
- iaml 10y ago
  Nvidia is doing a pretty damn good job at staying the only viable choice for machine learning. Or amd's lack of action is, anyway.

by mastazi 10y ago

p1esk 10y ago

jfsantos 10y ago

At the current state of things, AMD is definitely not a viable route, but that might change in the future with the "Boltzmann Initiative" [1]. Performance with OpenCL is not comparable with CUDA on NVIDIA GPUs at the moment, and support is lacking in most deep learning frameworks. [1] http://www.amd.com/en-us/press-releases/Pages/boltzmann-initiative-2015nov16.aspx http://www.amd.com/en-us/press-releases/Pages/boltzmann-init...

mastazi 10y ago
Thanks, your statement about performance is very helpful. Basically even if my tech stack supported OpenCL I would still be better of with a CUDA-compatible card.

mastazi 10y ago

Thank you @jfsantos and @p1esk. I'm going for a model equipped with an Nvidia GTX card I guess...

SixSigma 10y ago

We used to have a saying "friends don't make friends run closed software". I guess those days have gone.

mastazi 10y ago
I hear you, and I really wish an open alternative became prevalent over CUDA.
iaml 10y ago
Nvidia is doing a pretty damn good job at staying the only viable choice for machine learning. Or amd's lack of action is, anyway.