3.5 KiB
https://www.nvidia.com/Download/index.aspx
https://github.com/NVIDIA/nvidia-docker/wiki/Installation-(version-2.0)
https://github.com/NVIDIA/nvidia-docker/wiki/GPU-isolation-(version-1.0)
https://unix.stackexchange.com/questions/249643/gpu-usage-per-process-on-a-linux-machine-cuda
sudo yum install -y wget gcc pciutils git
sudo yum install -y kernel-devel-$(uname -r) kernel-headers-$(uname -r)
wget http://us.download.nvidia.com/tesla/410.129/NVIDIA-Linux-x86_64-410.129-diagnostic.run
sudo bash NVIDIA-Linux-x86_64-410.129-diagnostic.run
curl -fsSL https://get.docker.com | sh
sudo usermod -aG docker $USER
distribution=$(. /etc/os-release;echo $ID$VERSION_ID) curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.repo | sudo tee /etc/yum.repos.d/nvidia-docker.repo
sudo yum install -y nvidia-container-toolkit sudo systemctl restart docker
git clone https://github.com/tensorflow/models.git
docker run --gpus all -it --rm --mount type=bind,src=/home/newnius_cn/models,dst=/data tensorflow/tensorflow:1.14.0-gpu bash
docker run --gpus '"device=0,1"' -it --rm --mount type=bind,src=/home/newnius_cn/models,dst=/data tensorflow/tensorflow:1.14.0-gpu bash
export PYTHONPATH="$PYTHONPATH:/data"
pip install requests
mnist
python official/r1/mnist/mnist_test.py --benchmarks=.
CIFAR-10
python official/r1/resnet/cifar10_download_and_extract.py --data_dir /data/ds
python official/r1/resnet/cifar10_main.py --data_dir /data/ds/cifar-10-batches-bin --model_dir /tmp
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
config.log_device_placement = True
sess = tf.Session(config=config)
tf.keras.backend.set_session(sess)
sudo yum erase -y nvidia-container-runtime-hook.x86_64 nvidia-container-runtime.x86_64 nvidia-docker2.noarch docker-ce docker-ce-cli.x86_64
sudo gpg --homedir /var/lib/yum/repos/x86_64/7/libnvidia-container/gpgdir --delete-key F796ECB0
sudo gpg --homedir /var/lib/yum/repos/x86_64/7/nvidia-container-runtime/gpgdir --delete-key F796ECB0
sudo gpg --homedir /var/lib/yum/repos/x86_64/7/nvidia-docker/gpgdir --delete-key F796ECB0
Can not use nvidia-container-runtime repository - repomod.xml signature could not be verified
ERROR: Unable to load the kernel module 'nvidia.ko'. This happens most frequently when this kernel module was built against the wrong or improperly configured kernel sources, with a version of gcc that differs from the one used to build the target kernel, or if a driver such as rivafb, nvidiafb, or nouveau is present and prevents the NVIDIA kernel module from obtaining ownership of the NVIDIA graphics device(s), or no NVIDIA GPU installed in this system is supported by this NVIDIA Linux graphics driver release.
The problem is likely due to one of the issues listed in that error message. You'll need to go through them one by one, modifying things to rule them out.
blacklisting nouveau is frequently not enough. Often it is necessary to remove it from the initrd image as well.
as root:
echo -e "blacklist nouveau\noptions nouveau modeset=0" > /etc/modprobe.d/disable-nouveau.conf
update-initramfs -u
如果提示command not found，似乎没有关系，重启机器即可。
It looks like you did something like the first line already - that is the blacklist. The second line will remove it from the initrd image.
Section 8.1 of the driver README document discusses nouveau:
http://us.download.nvidia.com/XFree86/Linux-x86_64/340.24/README/index.html