kops/hooks/nvidia-device-plugin/image/files/01-aws-nvidia-driver.sh

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# Copyright 2017 The Kubernetes Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#!/bin/bash
set -euo pipefail
set -x
#################################################
# Settings
# A place on the host machine to cache 1.6GB+ downloads in-between reboots.
CACHE_DIR=/nvidia-device-plugin
# AWS Instance Types to Nvidia Card Mapping (cut and pasted from AWS docs)
# Load the correct driver for the correct instance type
# Instances Product Type Product Series Product
# G2 GRID GRID Series GRID K520 (deprecated)
# G3 Tesla M-Series M-60
# P2 Tesla K-Series K-80
# P3 Tesla V-Series V100
# http://www.nvidia.com/Download/index.aspx
declare -A class_to_driver_file
class_to_driver_file=( \
["g2"]="http://us.download.nvidia.com/XFree86/Linux-x86_64/367.124/NVIDIA-Linux-x86_64-367.124.run" \
["g3"]="http://us.download.nvidia.com/tesla/390.46/NVIDIA-Linux-x86_64-390.46.run" \
["p2"]="http://us.download.nvidia.com/tesla/390.46/NVIDIA-Linux-x86_64-390.46.run" \
["p3"]="http://us.download.nvidia.com/tesla/390.46/NVIDIA-Linux-x86_64-390.46.run" \
)
declare -A class_to_driver_checksum
class_to_driver_checksum=( \
["g2"]="77f37939efeea4b6505842bed50445971992e303" \
["g3"]="57569ecb6f6d839ecc77fa10a2c573cc069990cc" \
["p2"]="57569ecb6f6d839ecc77fa10a2c573cc069990cc" \
["p3"]="57569ecb6f6d839ecc77fa10a2c573cc069990cc" \
)
# CUDA Files that need to be installed ~1.4GB
# First one is main installation
# Subsequent files are patches which need to be applied in order
# Order in the arrays below matters
# https://developer.nvidia.com/cuda-downloads
cuda_files=( \
"https://developer.nvidia.com/compute/cuda/9.1/Prod/local_installers/cuda_9.1.85_387.26_linux" \
"https://developer.nvidia.com/compute/cuda/9.1/Prod/patches/1/cuda_9.1.85.1_linux" \
"https://developer.nvidia.com/compute/cuda/9.1/Prod/patches/2/cuda_9.1.85.2_linux" \
"https://developer.nvidia.com/compute/cuda/9.1/Prod/patches/3/cuda_9.1.85.3_linux" \
)
cuda_files_checksums=( \
"1540658f4fe657dddd8b0899555b7468727d4aa8" \
"7ec6970ecd81163b0d02ef30d35599e7fd6e97d8" \
"cfa3b029b58fc117d8ce510a70efc848924dd565" \
"6269a2c5784b08997edb97ea0020fb4e6c8769ed" \
)
containsElement () { for e in "${@:2}"; do [[ "$e" = "$1" ]] && return 0; done; return 1; }
#################################################
# Ensure that we are on a proper AWS GPU Instance
apt-get -y update
apt-get -y --no-upgrade install curl jq
AWS_INSTANCE_TYPE=$(curl -m 2 -fsSL http://169.254.169.254/latest/dynamic/instance-identity/document | jq -r ".instanceType" || true) # eg: p2.micro
AWS_INSTANCE_CLASS=$(echo $AWS_INSTANCE_TYPE | cut -d . -f 1 || true) # e.g. p2
if [[ -z $AWS_INSTANCE_TYPE ]] || [[ -z $AWS_INSTANCE_CLASS ]]; then
echo "This machine is not an AWS instance"
echo " Exiting without installing GPU drivers"
exit 1
fi
classnames=${!class_to_driver_file[@]} # e.g. [ "g2", "g3", "p2", "p3" ]
if ! containsElement $AWS_INSTANCE_CLASS $classnames; then
echo "This machine is an AWS instance, but not a GPU instance"
echo " Exiting without installing GPU drivers"
exit 1
fi
echo "Identified machine as AWS_INSTANCE_TYPE[$AWS_INSTANCE_TYPE] AWS_INSTANCE_CLASS[$AWS_INSTANCE_CLASS]"
#################################################
# Install dependencies
# Install GCC and linux headers on the host machine
# The NVIDIA driver build must be compiled with the same version of GCC as
# the kernel. In addition, linux-headers are machine image specific.
# Install with --no-upgrade so that the c-libs are not upgraded, possibly
# breaking programs and requiring restart
apt-get -y update
apt-get -y --no-upgrade install gcc libc-dev linux-headers-$(uname -r)
apt-get -y clean
apt-get -y autoremove
#################################################
# Unload open-source nouveau driver if it exists
# The nvidia drivers won't install otherwise
# "g3" instances in particular have this module auto-loaded
modprobe -r nouveau || true
#################################################
# Download and install the Nvidia drivers and cuda libraries
# Create list of URLs and Checksums by merging driver item with array of cuda files
downloads=(${class_to_driver_file[$AWS_INSTANCE_CLASS]} ${cuda_files[@]})
checksums=(${class_to_driver_checksum[$AWS_INSTANCE_CLASS]} ${cuda_files_checksums[@]})
# Download, verify, and execute each file
length=${#downloads[@]}
for (( i=0; i<${length}; i++ )); do
download=${downloads[$i]}
checksum=${checksums[$i]}
filename=$(basename $download)
filepath="${CACHE_DIR}/${filename}"
filepath_installed="${CACHE_DIR}/${filename}.installed"
echo "Checking for file at $filepath"
if [[ ! -f $filepath ]] || ! (echo "$checksum $filepath" | sha1sum -c - 2>&1 >/dev/null); then
echo "Downloading $download"
curl -L $download > $filepath
chmod a+x $filepath
fi
echo "Verifying sha1sum of file at $filepath"
if ! (echo "$checksum $filepath" | sha1sum -c -); then
echo "Failed to verify sha1sum for file at $filepath"
exit 1
fi
# Install the Nvidia driver and cuda libs
if [[ -f $filepath_installed ]]; then
echo "Detected prior install of file $filename on host"
else
echo "Installing file $filename on host"
if [[ $download =~ .*NVIDIA.* ]]; then
# Install the nvidia package
$filepath --accept-license --silent
touch $filepath_installed # Mark successful installation
elif [[ $download =~ .*local_installers.*cuda.* ]]; then
# Install the primary cuda library
$filepath --toolkit --silent --verbose
touch $filepath_installed # Mark successful installation
elif [[ $download =~ .*patches.*cuda.* ]]; then
# Install an update to the primary cuda library
$filepath --accept-eula --silent
touch $filepath_installed # Mark successful installation
else
echo "Unable to handle file $filepath"
exit 1
fi
fi
done
#################################################
# Output GPU info for debugging
nvidia-smi --list-gpus
#################################################
# Configure and Optimize Nvidia cards now that things are installed
# AWS Optimizization Doc
# https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/optimize_gpu.html
# Nvidia Doc
# http://developer.download.nvidia.com/compute/DCGM/docs/nvidia-smi-367.38.pdf
# Common configurations
nvidia-smi -pm 1
nvidia-smi --auto-boost-default=0
nvidia-smi --auto-boost-permission=0
# Custom configurations per class of nvidia video card
case "$AWS_INSTANCE_CLASS" in
"g2" | "g3")
nvidia-smi -ac 2505,1177
;;
"p2")
nvidia-smi -ac 2505,875
nvidia-smi -acp 0
;;
"p3")
nvidia-smi -ac 877,1530
nvidia-smi -acp 0
;;
*)
;;
esac
#################################################
# Load the Kernel Module
if ! /sbin/modprobe nvidia-uvm; then
echo "Unable to modprobe nvidia-uvm"
exit 1
fi
# Ensure that the device node exists
if ! test -e /dev/nvidia-uvm; then
# Find out the major device number used by the nvidia-uvm driver
D=`grep nvidia-uvm /proc/devices | awk '{print $1}'`
mknod -m 666 /dev/nvidia-uvm c $D 0
fi
###########################################################
# Restart Kubelet
# Only necessary in the case of Accelerators (not Device Plugins)
echo "Restarting Kubelet"
systemctl restart kubelet.service