What is the difference between cuda-toolkit-10-1 and nvidia-cuda-toolkit when I install it on Ubuntu 20.04?
Background of my questions
I have an old Lenovo ThinkPad W530 laptop with NVIDIA Corporation GK107GLM [Quadro K1000M] / Quadro K1000M/PCIe/SSE2 GPU which is with compute compatibility 3.0 and is supporting CUDA. I want to build some TensorFlow examples and project on Ubuntu for my Udacity nanodegree.
I just installed Ubuntu 20.04 and upgraded my NVIDIA drivers so when I execute nvidia-smi it gives me the following result:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.51.05 Driver Version: 450.51.05 CUDA Version: 11.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Quadro K1000M On | 00000000:01:00.0 Off | N/A |
| N/A 59C P0 N/A / N/A | 496MiB / 1999MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 5470 G /usr/lib/xorg/Xorg 39MiB |
| 0 N/A N/A 7504 G /usr/lib/xorg/Xorg 146MiB |
| 0 N/A N/A 7772 G /usr/bin/gnome-shell 147MiB |
| 0 N/A N/A 34770 G /proc/self/exe 158MiB |
+-----------------------------------------------------------------------------+As I am trying to build the TensorFlow Code using GPU support, I found out that I need to install CUDA and follow this article about how to install latest version of CUDA 11.0 on Ubuntu 20.04. I went through the whole path and then I found out two problems:
- My GPU is only support Compute Compatibility 3.0 while the minimum support for TensorFlow is 3.5
- To overcome problem 1, I have to build the tensor flow from sources to get a build that supports CUDA 3.0 and to do that I have to use CUDA 10.1 which means I have to start from the beginning.
I removed CUDA 11.0 following the CUDA documentation. I started to install CUDA 10.1 on Ubuntu 20.04 and now I got confused.
CUDA 10.1 installation documentation process is about installing CUDA 10.1 from a .deb file for Ubuntu 18.04 and there is no support for CUDA 10.1 on Ubuntu 20.04.
So I started to follow the same steps of the article but for CUDA 10.1 instead CUDA 11. I was able to install cuda 10.1 using the command:
sudo apt-get -f install cuda-toolkit-10-1 cuda-libraries-10-1so that I don't override my installed NVIDIA driver 450 (I did that after several trials).
When I tried to execute command
sudo apt install nvidia-cuda-toolkitIt gave me errors due to dependency problems. To overcome these errors I searched for a solution and then I came across this article which is recommending that:
For the sake of being verbose, do not try to use 18.10 or 18.04 CUDA 10.1 for Ubuntu 20.04. I learned that the hard way, lol!
So, you can install CUDA 10.1 in Ubuntu 20.04 by running,
$ sudo apt install nvidia-cuda-toolkit
I uninstalled CUDA Toolkit 10.1 that I installed using CUDA documentation and I followed this recommendation and the command passed successfully. But now I am not sure if this is it, or am I missing something?!
When I tried to know the different between both ways I found out that the source of nvidia-cuda-toolkit using the command
apt-cache policy nvidia-cuda-toolkitit gives me the following result that indicates that the source is the Ubuntu repositories
nvidia-cuda-toolkit: Installed: 10.1.243-3 Candidate: 10.1.243-3 Version table: *** 10.1.243-3 500 500 focal/multiverse amd64 Packages 100 /var/lib/dpkg/statusMy Questions
- If the official installation documentation of CUDA 10.1 for Ubuntu 18.04 as well as CUDA 11 for Ubuntu 20.04 doesn't indicate any thing regarding installing the package of
nvidia-cuda-toolkitso what is the difference betweennvidia-cuda-toolkitandcuda-toolkit-10-1? - Is it enough as indicated by the article to only install
nvidia-cuda-toolkitif I am trying to use CUDA toolkit 10.1? - Is CUDA 10.1 runtime libraries are now installed? If not, How can I install them right now? should I remove the
nvidia-cuda-toolkitor can I follow the steps from the documentation? - How can I validate my installation?
- When I tried to build CUDA Samples, didn't find the
cuda-install-samples-10.1.shfile in my installation. How can I install the samples?
I have been working on trying to build my examples and so far I failed to do that, so I really appreciate your support for this.
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