tested for two times.
prepare
- download os from aliyun: http://mirrors.aliyun.com/ubuntu-releases/2
- choose amd64 desktop version
- download qv2ray and v2ray core from github
- download ultraiso
- download cuda.run for your ubuntu version
use a portable disk to save all the files in case next time you need them
install ubuntu
- prepare a blank usb flash disk
- open the os iso in ultraios, and write it to your usb flash disk
- compress a blank partition in other disks, compress a 200m partition in your windows-disk
- reboot, in bois, select the usb flash disk, reboot
- edit install config(press
e
), addnomodeset
afterquite splash
( or it will 花屏) - f10 to reboot
- begin install
- choose the last option for install
- add ubuntu disk partitions on your blank partition
- /, main partition
- home, logistic partition
- add efi on 200m partition
- add swap if your ram is small
- after installation reboot
- in grub, edit again, use
e
, addnomodeset
afterquite splash
install cuda and graphic card driver
tutorials on Chinese websites are not good enough. they always said you need to install the driver first, but actually the cuda will recommend you to install the driver while you are installing cuda
copy the cuda.run from your external disk to your local disk
change directory to where your cuda is
sudo chmod x+a cuda.run
sudo ./cuda.run
after installation, edit environment variables
sudo gedit /etc/profile
, append contents like in the bottom
refer to https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#post-installation-actions for more
1 | export PATH=/usr/local/cuda-11.1/bin${PATH:+:${PATH}} |
source /etc/profile
to make it activated
check
use
nvidia-smi
andnvcc -V
to check whether it works.now you would be able to reboot the system without the need to add
nomodeset
run cuda examples
cd ~/nvidia_cuda-11.1-examples
make
devicequery
, it is under utilities/devicequery
install docker
https://docs.docker.com/engine/install/ubuntu/
1 | sudo apt-get update |
check
sudo docker run hello-world
add permission
1 | sudo gpasswd -a current_user_name docker |
install others, just follow the document
- ngc
- nvidia docker
use vm to boost local docker pull
- cd to
vm_for_docker_pull
( it is from my private repo) - in bash,
ssh -i nessvm-asia_key.pem ness@52.175.13.200
- pull the containers from NGC
docker tag image_from_ngc registry.cn-hangzhou.aliyuncs.com/ness001/image_name
- on your local computer,
docker pull registry.cn-hangzhou.aliyuncs.com/ness001/image_name
current pushed images
registry.cn-hangzhou.aliyuncs.com/ness001/
+aliyun image name
original name | tag | aliyun image name | usage |
---|---|---|---|
nvcr.io/nvidia/tlt-streamanalytics | v2.0_py3 | nv-tlt | transfer learning toolkit |
nvidia/cuda | 11.0-base | cuda11 | test for nvidia-docker2 |