Installing a Tesla Driver and CUDA Toolkit on a GPU-accelerated ECS¶
Scenarios¶
Before using a GPU-accelerated ECS, make sure that the desired Tesla driver and CUDA toolkit have been installed on the ECS for computing acceleration.
A computing-accelerated (P series) ECS created using a Windows public image has had a Tesla driver of a specified version installed by default.
A computing-accelerated (P series) ECS created using a Linux public image does not have a Tesla driver installed by default. After the ECS is created, install a driver on it for computing acceleration.
After a GPU-accelerated ECS is created using a private image, it must have a Tesla driver installed. Otherwise, computing acceleration will not take effect.
This section describes how to install a Tesla driver and CUDA toolkit on a GPU-accelerated ECS.
Notes¶
The ECS must have an EIP bound.
Check whether the CUDA toolkit and Tesla driver have been installed on the ECS.
Note
If the CUDA toolkit has not been installed, download it from the official NVIDIA website and install it. A Tesla driver matching the CUDA version will be automatically installed then. However, if there are specific requirements or dependencies on the Tesla driver version, download the matching Tesla driver from the official NVIDIA website first and then install the driver before installing the CUDA toolkit.
If a Tesla driver has been installed on the ECS, check the driver version. Before installing a new driver version, uninstall the original Tesla driver to prevent an installation failure due to driver conflicts.
Installation process:
Installing a Tesla Driver on a Linux ECS¶
The following uses Ubuntu 16.04 64bit as an example to describe how to install the Tesla driver matching CUDA 10.1 on a GPU-accelerated ECS.
Note
The Linux kernel version is compatible with the driver version. If installing the driver failed, check the driver installation log, which is generally stored in /var/log/nvidia-installer.log. If the log shows that the failure was caused by a driver compilation error, for example, the get_user_pages parameter setting is incorrect, the kernel version is incompatible with the driver version. In such a case, select the desired kernel version and driver version and reinstall them. It is recommended that the release time of the kernel version and driver version be the same.
Log in to the ECS.
Update the system software based on the OS.
Ubuntu
Update the software installation source: apt-get -y update
Install necessary programs: apt-get install gcc g++ make
CentOS
Update the software installation source: yum -y update --exclude=kernel* --exclude=centos-release* --exclude=initscripts*
Install the desired program: yum install -y kernel-devel-`uname -r` gcc gcc-c++
Download the NVIDIA driver package.
Select a driver version at NVIDIA Driver Downloads based on the ECS type. Click SEARCH.
Select a driver version as required. The following uses Tesla 418.67 as an example.
Click the driver to be downloaded. On the TESLA DRIVER FOR LINUX X64 page that is displayed, click DOWNLOAD.
Copy the download link.
Run the following command on the ECS to download the driver:
wget Copied link
For example, wget http://us.download.nvidia.com/tesla/418.67/NVIDIA-Linux-x86_64-418.67.run
Run the following command to install the driver:
sh NVIDIA-Linux-x86_64-418.67.run
(Optional) If the following information is displayed after the command for installing the driver is executed, disable the Nouveau driver.
Run the following command to check whether the Nouveau driver has been installed:
lsmod | grep nouveau
Edit the blacklist.conf file.
If the /etc/modprobe.d/blacklist.conf file is unavailable, create it.
vi /etc/modprobe.d/blacklist.conf
Add the following statement to the end of the file:
blacklist nouveau options nouveau modeset=0
Run the following command to back up and create an initramfs application:
Ubuntu
sudo update-initramfs -u
CentOS:
mv /boot/initramfs-$(uname -r).img /boot/initramfs-$(uname -r).img.bak
dracut -v /boot/initramfs-$(uname -r).img $(uname -r)
Restart the ECS:
reboot
Select OK for three consecutive times as prompted to complete the driver installation.
Run the following command to set systemd:
systemctl set-default multi-user.target
Run the reboot command to restart the ECS.
Log in to the ECS and run the nvidia-smi command. If the command output contains the installed driver version, the driver has been installed.
Installing a Tesla Driver on a Windows ECS¶
The following uses Windows Server 2016 Standard 64bit as an example to describe how to install a Tesla driver on a GPU-accelerated ECS.
Log in to the ECS.
Download the NVIDIA driver package.
Select a driver version at NVIDIA Driver Downloads based on the ECS type.
Select a driver version as required. The following uses Tesla 425.25 as an example.
Click the driver to be downloaded. On the TESLA DRIVER FOR WINDOWS page that is displayed, click DOWNLOAD.
Click AGREE & DOWNLOAD to download the installation package.
Double-click the driver and click Run.
Select an installation path and click OK.
Install the NVIDIA program as prompted.
Restart the ECS.
Check whether the NVIDIA driver has been installed.
Switch to Device Manager and click Display adapters.
Open the cmd window on the ECS and run the following commands:
cd C:\Program Files\NVIDIA Corporation\NVSMI
nvidia-smi
If the command output contains the installed driver version, the driver has been installed.
Installing the CUDA Toolkit on a Linux ECS¶
The following uses Ubuntu 16.04 64bit as an example to describe how to install the CUDA 10.1 toolkit on a GPU-accelerated ECS.
Log in to the ECS.
Update the system software based on the OS.
Ubuntu
Update the software installation source: apt-get -y update
Install necessary programs: apt-get install gcc g++ make
CentOS
Update the software installation source: yum -y update --exclude=kernel* --exclude=centos-release* --exclude=initscripts*
Install the desired program: yum install -y kernel-devel-`uname -r` gcc gcc-c++
On the CUDA download page, set parameters according to the information shown in Obtaining a Tesla Driver and CUDA Toolkit.
Find the link for downloading CUDA 10.1 and copy the link.
Run the following command on the ECS to download CUDA:
wget Copied link
For example, wget https://developer.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda_10.1.105_418.39_linux.run
Install CUDA.
Follow the instructions provided on the official NVIDIA website.
Run the following command to install CUDA:
sh cuda_10.1.243_418.87.00_linux.run
Select accept on the installation page and press Enter.
Select Install and press Enter to start the installation.
Run the following command to switch to /usr/local/cuda-10.1/samples/1_Utilities/deviceQuery:
cd /usr/local/cuda-10.1/samples/1_Utilities/deviceQuery
Run the make command to automatically compile the deviceQuery program.
Run the following command to check whether CUDA has been installed:
./deviceQuery
If the command output contains the CUDA version, CUDA has been installed.
Check the CUDA version.
/usr/local/cuda/bin/nvcc -V
Run the following command to enable the persistent mode:
sudo nvidia-smi -pm 1
Enabling the persistent mode optimizes the GPU performance on Linux ECSs.
Installing the CUDA Toolkit on a Windows ECS¶
The following uses Windows Server 2016 Standard 64bit as an example to describe how to install the CUDA 10.1 toolkit on a GPU-accelerated ECS.
Log in to the ECS.
On the CUDA download page, set parameters according to the information shown in Downloading a CUDA Toolkit.
Find the link for downloading CUDA 10.1.
Click Download to download the CUDA toolkit.
Double-click the installation file and click Run to install the CUDA toolkit.
On the CUDA Setup Package page, select an installation path and click OK.
Install the CUDA toolkit as prompted.
Check whether CUDA has been installed
Open the cmd window and run the following command:
nvcc -V
If the command output contains the CUDA version, CUDA has been installed.