Installation
Step 1. Pre-installation Actions
In this step, please check whether your system is cuda-supported.
Note:
- gcc version is important, please refer to Table 1 in the link. Recommend: gcc-7.
- See Error case 1 to check and set default gcc version.
- When downloading cuda-toolkit, recommend to use runfile(local), because for some reason, I tried deb(local) and deb(network), both failed.
Step 2. Package Manager Installation
If you use runfile(local), then there is no need to Install repository meta-data and Installing the CUDA public GPG key. You can directly execute:
1
2
sudo apt-get update
sudo apt-get install cuda
If the installation is broken, try:
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sudo apt --fix-broken install
Step 3. Check installation
You can check whether you have successfully installed cuda by:
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nvidia-smi
Then you will get something like this:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.33.01 Driver Version: 440.33.01 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce RTX 2060 On | 00000000:01:00.0 On | N/A |
| 45% 35C P8 10W / 160W | 1062MiB / 5931MiB | 2% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 1174 G /usr/lib/xorg/Xorg 40MiB |
| 0 1309 G /usr/bin/gnome-shell 51MiB |
| 0 1536 G /usr/lib/xorg/Xorg 511MiB |
| 0 1679 G /usr/bin/gnome-shell 174MiB |
| 0 2165 G ...quest-channel-token=1797818128468897323 160MiB |
| 0 3936 G ...uest-channel-token=17969104812798294633 118MiB |
+-----------------------------------------------------------------------------+
Step 4 Set environment variables
The PATH variable needs to include /usr/local/cuda-10.2/bin and /usr/local/cuda-10.2/NsightCompute-. refers to the version of Nsight Compute that ships with the CUDA toolkit, e.g. 2019.1.
To add this path to the PATH variable:
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$ export PATH=/usr/local/cuda-10.2/bin:/usr/local/cuda-10.2/NsightCompute-2019.1${PATH:+:${PATH}}
In addition, when using the runfile installation method, the LD_LIBRARY_PATH variable needs to contain /usr/local/cuda-10.2/lib64 on a 64-bit system, or /usr/local/cuda-10.2/lib on a 32-bit system
- To change the environment variables for 64-bit operating systems:12$ export LD_LIBRARY_PATH=/usr/local/cuda-10.2/lib64\ ${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
- To change the environment variables for 32-bit operating systems:12$ export LD_LIBRARY_PATH=/usr/local/cuda-10.2/lib\ ${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
Error cases
1. Modify default gcc version
Step 1. Install different gcc versions using apt-get, for example:
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sudo apt-get install gcc-4.8
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sudo apt-get install gcc-7
Step 2. Check if gcc is installed successfully:
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gcc --verison
or
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gcc-7 --version
Step 3. Check priority of gcc1
sudo update-alternatives --config gcc
You can see something like this:8
There are 2 choices for the alternative gcc (providing /usr/bin/gcc).
Step 4. Modify priority of gcc
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sudo update-alternative --install /usr/bin/gcc gcc /usr/bin/gcc-7 100
Then you can see the priority of gcc-7 is set to be 100. You can check using the command in Step 3.
Regards,
Rachel Gomez
